# The Handbook

> The definitive technical interview resource for ML, AI, and Software Engineering roles

## SDE Coding

- [Overview](https://abhinaavramesh.github.io/handbook/sde-coding/)
- [Interview Tips](https://abhinaavramesh.github.io/handbook/sde-coding/overview/interview-tips.html)
- [Choosing a Language](https://abhinaavramesh.github.io/handbook/sde-coding/overview/choosing-language.html)
- [Java-Specific Pointers](https://abhinaavramesh.github.io/handbook/sde-coding/overview/java-specific-pointers.html)
- [Practice Warm-Up](https://abhinaavramesh.github.io/handbook/sde-coding/overview/practice-warmup.html)
- [Overview](https://abhinaavramesh.github.io/handbook/sde-coding/fast-track/)
- [Week 1: Foundations](https://abhinaavramesh.github.io/handbook/sde-coding/fast-track/week1-foundations.html)
- [Week 2: Advanced](https://abhinaavramesh.github.io/handbook/sde-coding/fast-track/week2-advanced.html)
- [Essential Patterns](https://abhinaavramesh.github.io/handbook/sde-coding/fast-track/essential-patterns.html)
- [Priority Problems](https://abhinaavramesh.github.io/handbook/sde-coding/fast-track/priority-problems.html)
- [How to Answer Questions](https://abhinaavramesh.github.io/handbook/sde-coding/fast-track/answering-questions.html)
- [Arrays & Pointers](https://abhinaavramesh.github.io/handbook/sde-coding/fast-track/arrays-pointers-stacks.html)
- [Binary Search & Heaps](https://abhinaavramesh.github.io/handbook/sde-coding/fast-track/binary-search-heaps.html)
- [Lists, Trees & Tries](https://abhinaavramesh.github.io/handbook/sde-coding/fast-track/lists-trees-tries.html)
- [Backtracking, Graphs & DP](https://abhinaavramesh.github.io/handbook/sde-coding/fast-track/backtracking-graphs-dp.html)
- [Mock Interview Guide](https://abhinaavramesh.github.io/handbook/sde-coding/fast-track/mock-interview-guide.html)
- [Day-of Checklist](https://abhinaavramesh.github.io/handbook/sde-coding/fast-track/day-of-checklist.html)
- [Common Mistakes](https://abhinaavramesh.github.io/handbook/sde-coding/fast-track/common-mistakes.html)
- [Overview](https://abhinaavramesh.github.io/handbook/sde-coding/sprint/)
- [Study Schedule](https://abhinaavramesh.github.io/handbook/sde-coding/sprint/schedule.html)
- [Graphs (Tier 1)](https://abhinaavramesh.github.io/handbook/sde-coding/sprint/graphs.html)
- [Trees (Tier 2)](https://abhinaavramesh.github.io/handbook/sde-coding/sprint/trees.html)
- [Sliding Window (Tier 3)](https://abhinaavramesh.github.io/handbook/sde-coding/sprint/sliding-window.html)
- [DP (Tier 4)](https://abhinaavramesh.github.io/handbook/sde-coding/sprint/dp.html)
- [HashMap/Heap/BS (Tier 5)](https://abhinaavramesh.github.io/handbook/sde-coding/sprint/data-structures.html)
- [Strings (Tier 6)](https://abhinaavramesh.github.io/handbook/sde-coding/sprint/strings.html)
- [Code Templates](https://abhinaavramesh.github.io/handbook/sde-coding/sprint/templates.html)
- [Interview Day](https://abhinaavramesh.github.io/handbook/sde-coding/sprint/interview-day.html)
- [Big O & Time](https://abhinaavramesh.github.io/handbook/sde-coding/complexity/big-o-time.html)
- [Space & Optimization](https://abhinaavramesh.github.io/handbook/sde-coding/complexity/space-optimization.html)
- [Overview](https://abhinaavramesh.github.io/handbook/sde-coding/patterns/)
- [Two Pointers](https://abhinaavramesh.github.io/handbook/sde-coding/patterns/two-pointers.html)
- [Sliding Window](https://abhinaavramesh.github.io/handbook/sde-coding/patterns/sliding-window.html)
- [Prefix Sum & Cycle Detection](https://abhinaavramesh.github.io/handbook/sde-coding/patterns/prefix-sum-cycle.html)
- [Bit Manipulation & Cyclic Sort](https://abhinaavramesh.github.io/handbook/sde-coding/patterns/bit-manipulation-cyclic.html)
- [Overview](https://abhinaavramesh.github.io/handbook/sde-coding/arrays/)
- [Two Sum](https://abhinaavramesh.github.io/handbook/sde-coding/arrays/two-sum.html)
- [Three Sum](https://abhinaavramesh.github.io/handbook/sde-coding/arrays/three-sum.html)
- [Buy Sell Stock](https://abhinaavramesh.github.io/handbook/sde-coding/arrays/buy-sell-stock.html)
- [Contains Duplicate](https://abhinaavramesh.github.io/handbook/sde-coding/arrays/contains-duplicate.html)
- [Product Except Self](https://abhinaavramesh.github.io/handbook/sde-coding/arrays/product-except-self.html)
- [Maximum Subarray](https://abhinaavramesh.github.io/handbook/sde-coding/arrays/maximum-subarray.html)
- [Merge Intervals](https://abhinaavramesh.github.io/handbook/sde-coding/arrays/merge-intervals.html)
- [Container Water](https://abhinaavramesh.github.io/handbook/sde-coding/arrays/container-water.html)
- [Trapping Rain Water](https://abhinaavramesh.github.io/handbook/sde-coding/arrays/trapping-rain-water.html)
- [Rotate Array](https://abhinaavramesh.github.io/handbook/sde-coding/arrays/rotate-array.html)
- [Move Zeros](https://abhinaavramesh.github.io/handbook/sde-coding/arrays/move-zeros.html)
- [Remove Duplicates](https://abhinaavramesh.github.io/handbook/sde-coding/arrays/remove-duplicates.html)
- [Find Peak](https://abhinaavramesh.github.io/handbook/sde-coding/arrays/find-peak.html)
- [Search Rotated](https://abhinaavramesh.github.io/handbook/sde-coding/arrays/search-rotated.html)
- [First Missing Positive](https://abhinaavramesh.github.io/handbook/sde-coding/arrays/first-missing-positive.html)
- [Median Two Arrays](https://abhinaavramesh.github.io/handbook/sde-coding/arrays/median-two-arrays.html)
- [Sliding Window Max](https://abhinaavramesh.github.io/handbook/sde-coding/arrays/sliding-window-max.html)
- [Subarray Sum K](https://abhinaavramesh.github.io/handbook/sde-coding/arrays/subarray-sum-k.html)
- [Merge Intervals & Anagrams](https://abhinaavramesh.github.io/handbook/sde-coding/arrays/merge-intervals-anagrams.html)
- [Product & Spiral](https://abhinaavramesh.github.io/handbook/sde-coding/arrays/product-spiral.html)
- [Subarray & Container](https://abhinaavramesh.github.io/handbook/sde-coding/arrays/subarray-container.html)
- [Task Scheduler & Rain Water](https://abhinaavramesh.github.io/handbook/sde-coding/arrays/task-scheduler-rain.html)
- [Overview](https://abhinaavramesh.github.io/handbook/sde-coding/hash-tables/)
- [Two Sum](https://abhinaavramesh.github.io/handbook/sde-coding/hash-tables/two-sum.html)
- [Valid Anagram](https://abhinaavramesh.github.io/handbook/sde-coding/hash-tables/valid-anagram.html)
- [Group Anagrams](https://abhinaavramesh.github.io/handbook/sde-coding/hash-tables/group-anagrams.html)
- [Contains Duplicate](https://abhinaavramesh.github.io/handbook/sde-coding/hash-tables/contains-duplicate.html)
- [Top K Frequent](https://abhinaavramesh.github.io/handbook/sde-coding/hash-tables/top-k-frequent.html)
- [Longest Substring](https://abhinaavramesh.github.io/handbook/sde-coding/hash-tables/longest-substring.html)
- [Longest Consecutive](https://abhinaavramesh.github.io/handbook/sde-coding/hash-tables/longest-consecutive.html)
- [Subarray Sum K](https://abhinaavramesh.github.io/handbook/sde-coding/hash-tables/subarray-sum-k.html)
- [Minimum Window](https://abhinaavramesh.github.io/handbook/sde-coding/hash-tables/minimum-window.html)
- [LRU Cache](https://abhinaavramesh.github.io/handbook/sde-coding/hash-tables/lru-cache.html)
- [Design HashMap](https://abhinaavramesh.github.io/handbook/sde-coding/hash-tables/design-hashmap.html)
- [Design File System](https://abhinaavramesh.github.io/handbook/sde-coding/hash-tables/design-file-system.html)
- [All O One](https://abhinaavramesh.github.io/handbook/sde-coding/hash-tables/all-oone.html)
- [First Non Repeating](https://abhinaavramesh.github.io/handbook/sde-coding/hash-tables/first-non-repeating.html)
- [Four Sum II](https://abhinaavramesh.github.io/handbook/sde-coding/hash-tables/four-sum-ii.html)
- [Copy Random List](https://abhinaavramesh.github.io/handbook/sde-coding/hash-tables/copy-random-list.html)
- [Ransom Note](https://abhinaavramesh.github.io/handbook/sde-coding/hash-tables/ransom-note.html)
- [Max Profit](https://abhinaavramesh.github.io/handbook/sde-coding/hash-tables/max-profit.html)
- [Two Sum & Profit](https://abhinaavramesh.github.io/handbook/sde-coding/hash-tables/two-sum-profit.html)
- [Advanced Hash Problems](https://abhinaavramesh.github.io/handbook/sde-coding/hash-tables/advanced-hash.html)
- [Overview](https://abhinaavramesh.github.io/handbook/sde-coding/searching-sorting/)
- [Sorting Algorithms](https://abhinaavramesh.github.io/handbook/sde-coding/searching-sorting/sorting-algorithms.html)
- [Binary Search](https://abhinaavramesh.github.io/handbook/sde-coding/searching-sorting/binary-search.html)
- [Two Pointer](https://abhinaavramesh.github.io/handbook/sde-coding/searching-sorting/two-pointer.html)
- [Sliding Window](https://abhinaavramesh.github.io/handbook/sde-coding/searching-sorting/sliding-window.html)
- [Quick Select](https://abhinaavramesh.github.io/handbook/sde-coding/searching-sorting/quick-select.html)
- [Non-Comparison Sorts](https://abhinaavramesh.github.io/handbook/sde-coding/searching-sorting/non-comparison-sorts.html)
- [Merge Intervals](https://abhinaavramesh.github.io/handbook/sde-coding/searching-sorting/merge-intervals.html)
- [Rotated Array Search](https://abhinaavramesh.github.io/handbook/sde-coding/searching-sorting/rotated-array-search.html)
- [Rotated Arrays & Koko](https://abhinaavramesh.github.io/handbook/sde-coding/searching-sorting/rotated-koko.html)
- [K-Messed & Duplicates](https://abhinaavramesh.github.io/handbook/sde-coding/searching-sorting/kmessed-duplicates.html)
- [Overview](https://abhinaavramesh.github.io/handbook/sde-coding/strings/)
- [Reverse String](https://abhinaavramesh.github.io/handbook/sde-coding/strings/reverse-string.html)
- [First Unique Char](https://abhinaavramesh.github.io/handbook/sde-coding/strings/first-unique-char.html)
- [String to Integer](https://abhinaavramesh.github.io/handbook/sde-coding/strings/string-to-integer.html)
- [Longest Common Prefix](https://abhinaavramesh.github.io/handbook/sde-coding/strings/longest-common-prefix.html)
- [Longest Palindromic Substring](https://abhinaavramesh.github.io/handbook/sde-coding/strings/longest-palindromic-substring.html)
- [Group Anagrams](https://abhinaavramesh.github.io/handbook/sde-coding/strings/group-anagrams.html)
- [Anagram Problems](https://abhinaavramesh.github.io/handbook/sde-coding/strings/anagram-problems.html)
- [Minimum Window Substring](https://abhinaavramesh.github.io/handbook/sde-coding/strings/minimum-window-substring.html)
- [Edit Distance](https://abhinaavramesh.github.io/handbook/sde-coding/strings/edit-distance.html)
- [Regex Matching](https://abhinaavramesh.github.io/handbook/sde-coding/strings/regex-matching.html)
- [Wildcard Matching](https://abhinaavramesh.github.io/handbook/sde-coding/strings/wildcard-matching.html)
- [Palindrome Partitioning](https://abhinaavramesh.github.io/handbook/sde-coding/strings/palindrome-partitioning.html)
- [Palindrome & Common Words](https://abhinaavramesh.github.io/handbook/sde-coding/strings/palindrome-common.html)
- [IP Validation & Decrypt](https://abhinaavramesh.github.io/handbook/sde-coding/strings/ip-decrypt.html)
- [Window & Serialize](https://abhinaavramesh.github.io/handbook/sde-coding/strings/window-serialize.html)
- [Substring Problems](https://abhinaavramesh.github.io/handbook/sde-coding/strings/substring-problems.html)
- [Overview](https://abhinaavramesh.github.io/handbook/sde-coding/graphs/)
- [Clone Graph](https://abhinaavramesh.github.io/handbook/sde-coding/graphs/clone-graph.html)
- [Connected Components](https://abhinaavramesh.github.io/handbook/sde-coding/graphs/connected-components.html)
- [Cycle Detection](https://abhinaavramesh.github.io/handbook/sde-coding/graphs/cycle-detection.html)
- [Graph Valid Tree](https://abhinaavramesh.github.io/handbook/sde-coding/graphs/graph-valid-tree.html)
- [Network Delay](https://abhinaavramesh.github.io/handbook/sde-coding/graphs/network-delay.html)
- [Cheapest Flights](https://abhinaavramesh.github.io/handbook/sde-coding/graphs/cheapest-flights.html)
- [Pacific Atlantic](https://abhinaavramesh.github.io/handbook/sde-coding/graphs/pacific-atlantic.html)
- [Surrounded Regions](https://abhinaavramesh.github.io/handbook/sde-coding/graphs/surrounded-regions.html)
- [Word Ladder](https://abhinaavramesh.github.io/handbook/sde-coding/graphs/word-ladder.html)
- [Alien Dictionary](https://abhinaavramesh.github.io/handbook/sde-coding/graphs/alien-dictionary.html)
- [Graph Search & Friendship](https://abhinaavramesh.github.io/handbook/sde-coding/graphs/search-friendship.html)
- [Islands & Oranges](https://abhinaavramesh.github.io/handbook/sde-coding/graphs/islands-oranges.html)
- [Course Schedule & Edit Distance](https://abhinaavramesh.github.io/handbook/sde-coding/graphs/course-schedule-edit.html)
- [Redundant Connection](https://abhinaavramesh.github.io/handbook/sde-coding/graphs/redundant-connection.html)
- [Overview](https://abhinaavramesh.github.io/handbook/sde-coding/trees/)
- [BST Operations](https://abhinaavramesh.github.io/handbook/sde-coding/trees/bst-operations.html)
- [Construct & Serialize](https://abhinaavramesh.github.io/handbook/sde-coding/trees/construct-serialize.html)
- [Level Order & Zigzag](https://abhinaavramesh.github.io/handbook/sde-coding/trees/level-order-zigzag.html)
- [LCA & Path Sum](https://abhinaavramesh.github.io/handbook/sde-coding/trees/lca-path-sum.html)
- [Max Path Sum](https://abhinaavramesh.github.io/handbook/sde-coding/trees/max-path-sum.html)
- [Same Subtree & Invert](https://abhinaavramesh.github.io/handbook/sde-coding/trees/same-subtree-invert.html)
- [Good Nodes & Boundary](https://abhinaavramesh.github.io/handbook/sde-coding/trees/good-nodes-boundary.html)
- [Balanced, Diameter & Validate](https://abhinaavramesh.github.io/handbook/sde-coding/trees/balanced-diameter-validate.html)
- [Construct Tree & Trie](https://abhinaavramesh.github.io/handbook/sde-coding/trees/construct-trie.html)
- [LCA & BST Operations](https://abhinaavramesh.github.io/handbook/sde-coding/trees/lca-bst-operations.html)
- [Overview](https://abhinaavramesh.github.io/handbook/sde-coding/stacks-queues/)
- [Valid Parentheses](https://abhinaavramesh.github.io/handbook/sde-coding/stacks-queues/valid-parentheses.html)
- [Min Stack](https://abhinaavramesh.github.io/handbook/sde-coding/stacks-queues/min-stack.html)
- [Daily Temperatures](https://abhinaavramesh.github.io/handbook/sde-coding/stacks-queues/daily-temperatures.html)
- [Next Greater Element](https://abhinaavramesh.github.io/handbook/sde-coding/stacks-queues/next-greater-element.html)
- [Largest Rectangle Histogram](https://abhinaavramesh.github.io/handbook/sde-coding/stacks-queues/largest-rectangle-histogram.html)
- [Trapping Rain Water](https://abhinaavramesh.github.io/handbook/sde-coding/stacks-queues/trapping-rain-water.html)
- [Decode String](https://abhinaavramesh.github.io/handbook/sde-coding/stacks-queues/decode-string.html)
- [Simplify Path](https://abhinaavramesh.github.io/handbook/sde-coding/stacks-queues/simplify-path.html)
- [Asteroid Collision](https://abhinaavramesh.github.io/handbook/sde-coding/stacks-queues/asteroid-collision.html)
- [Basic Calculator](https://abhinaavramesh.github.io/handbook/sde-coding/stacks-queues/basic-calculator.html)
- [Basic Calculator II](https://abhinaavramesh.github.io/handbook/sde-coding/stacks-queues/basic-calculator-ii.html)
- [Reverse Polish Notation](https://abhinaavramesh.github.io/handbook/sde-coding/stacks-queues/reverse-polish-notation.html)
- [Remove K Digits](https://abhinaavramesh.github.io/handbook/sde-coding/stacks-queues/remove-k-digits.html)
- [Stock Span](https://abhinaavramesh.github.io/handbook/sde-coding/stacks-queues/stock-span.html)
- [Queue Using Stacks](https://abhinaavramesh.github.io/handbook/sde-coding/stacks-queues/queue-using-stacks.html)
- [Stack Using Queues](https://abhinaavramesh.github.io/handbook/sde-coding/stacks-queues/stack-using-queues.html)
- [Sliding Window Maximum](https://abhinaavramesh.github.io/handbook/sde-coding/stacks-queues/sliding-window-maximum.html)
- [Rotting Oranges](https://abhinaavramesh.github.io/handbook/sde-coding/stacks-queues/rotting-oranges.html)
- [Task Scheduler](https://abhinaavramesh.github.io/handbook/sde-coding/stacks-queues/task-scheduler.html)
- [First Negative Window](https://abhinaavramesh.github.io/handbook/sde-coding/stacks-queues/first-negative-window.html)
- [Parentheses & Min Stack](https://abhinaavramesh.github.io/handbook/sde-coding/stacks-queues/parentheses-stack.html)
- [Temperatures & Path](https://abhinaavramesh.github.io/handbook/sde-coding/stacks-queues/temperatures-path.html)
- [Overview](https://abhinaavramesh.github.io/handbook/sde-coding/linked-lists/)
- [Fast Slow Pointers](https://abhinaavramesh.github.io/handbook/sde-coding/linked-lists/fast-slow-pointers.html)
- [Merge Operations](https://abhinaavramesh.github.io/handbook/sde-coding/linked-lists/merge-operations.html)
- [Deletion Operations](https://abhinaavramesh.github.io/handbook/sde-coding/linked-lists/deletion-operations.html)
- [Reorder Operations](https://abhinaavramesh.github.io/handbook/sde-coding/linked-lists/reorder-operations.html)
- [Rotation Operations](https://abhinaavramesh.github.io/handbook/sde-coding/linked-lists/rotation-operations.html)
- [Swap Operations](https://abhinaavramesh.github.io/handbook/sde-coding/linked-lists/swap-operations.html)
- [Sort Operations](https://abhinaavramesh.github.io/handbook/sde-coding/linked-lists/sort-operations.html)
- [Intersection Operations](https://abhinaavramesh.github.io/handbook/sde-coding/linked-lists/intersection-operations.html)
- [Arithmetic Operations](https://abhinaavramesh.github.io/handbook/sde-coding/linked-lists/arithmetic-operations.html)
- [Advanced Operations](https://abhinaavramesh.github.io/handbook/sde-coding/linked-lists/advanced-operations.html)
- [Reverse K Group](https://abhinaavramesh.github.io/handbook/sde-coding/linked-lists/reverse-k-group.html)
- [LRU Cache](https://abhinaavramesh.github.io/handbook/sde-coding/linked-lists/lru-cache.html)
- [Reverse & Cycle](https://abhinaavramesh.github.io/handbook/sde-coding/linked-lists/reverse-cycle.html)
- [Merge & LRU Cache](https://abhinaavramesh.github.io/handbook/sde-coding/linked-lists/merge-lru.html)
- [Overview](https://abhinaavramesh.github.io/handbook/sde-coding/heaps/)
- [Kth Largest](https://abhinaavramesh.github.io/handbook/sde-coding/heaps/kth-largest.html)
- [Top K Frequent](https://abhinaavramesh.github.io/handbook/sde-coding/heaps/top-k-frequent.html)
- [K Closest Points](https://abhinaavramesh.github.io/handbook/sde-coding/heaps/k-closest-points.html)
- [Find Median Stream](https://abhinaavramesh.github.io/handbook/sde-coding/heaps/find-median-stream.html)
- [Merge K Sorted](https://abhinaavramesh.github.io/handbook/sde-coding/heaps/merge-k-sorted.html)
- [Meeting Rooms II](https://abhinaavramesh.github.io/handbook/sde-coding/heaps/meeting-rooms-ii.html)
- [Task Scheduler](https://abhinaavramesh.github.io/handbook/sde-coding/heaps/task-scheduler.html)
- [Reorganize String](https://abhinaavramesh.github.io/handbook/sde-coding/heaps/reorganize-string.html)
- [Smallest Range](https://abhinaavramesh.github.io/handbook/sde-coding/heaps/smallest-range.html)
- [Sliding Window Median](https://abhinaavramesh.github.io/handbook/sde-coding/heaps/sliding-window-median.html)
- [Heap Problems](https://abhinaavramesh.github.io/handbook/sde-coding/heaps/heap-problems.html)
- [Overview](https://abhinaavramesh.github.io/handbook/sde-coding/recursion-backtracking/)
- [Factorial](https://abhinaavramesh.github.io/handbook/sde-coding/recursion-backtracking/factorial.html)
- [Fibonacci](https://abhinaavramesh.github.io/handbook/sde-coding/recursion-backtracking/fibonacci.html)
- [Climbing Stairs](https://abhinaavramesh.github.io/handbook/sde-coding/recursion-backtracking/climbing-stairs.html)
- [Generate Parentheses](https://abhinaavramesh.github.io/handbook/sde-coding/recursion-backtracking/generate-parentheses.html)
- [Letter Combinations](https://abhinaavramesh.github.io/handbook/sde-coding/recursion-backtracking/letter-combinations.html)
- [Subsets](https://abhinaavramesh.github.io/handbook/sde-coding/recursion-backtracking/subsets.html)
- [Subsets II](https://abhinaavramesh.github.io/handbook/sde-coding/recursion-backtracking/subsets-ii.html)
- [Permutations](https://abhinaavramesh.github.io/handbook/sde-coding/recursion-backtracking/permutations.html)
- [Permutations II](https://abhinaavramesh.github.io/handbook/sde-coding/recursion-backtracking/permutations-ii.html)
- [Combination Sum](https://abhinaavramesh.github.io/handbook/sde-coding/recursion-backtracking/combination-sum.html)
- [Combination Sum II](https://abhinaavramesh.github.io/handbook/sde-coding/recursion-backtracking/combination-sum-ii.html)
- [Palindrome Partitioning](https://abhinaavramesh.github.io/handbook/sde-coding/recursion-backtracking/palindrome-partitioning.html)
- [Word Search](https://abhinaavramesh.github.io/handbook/sde-coding/recursion-backtracking/word-search.html)
- [Word Search II](https://abhinaavramesh.github.io/handbook/sde-coding/recursion-backtracking/word-search-ii.html)
- [N Queens](https://abhinaavramesh.github.io/handbook/sde-coding/recursion-backtracking/n-queens.html)
- [N Queens II](https://abhinaavramesh.github.io/handbook/sde-coding/recursion-backtracking/n-queens-ii.html)
- [Sudoku Solver](https://abhinaavramesh.github.io/handbook/sde-coding/recursion-backtracking/sudoku-solver.html)
- [Fibonacci, Parentheses & Subsets](https://abhinaavramesh.github.io/handbook/sde-coding/recursion-backtracking/fib-parentheses-subsets.html)
- [Permutations & Combinations](https://abhinaavramesh.github.io/handbook/sde-coding/recursion-backtracking/permutations-combinations.html)
- [Sudoku & Regex](https://abhinaavramesh.github.io/handbook/sde-coding/recursion-backtracking/sudoku-regex.html)
- [Calculator & Misc](https://abhinaavramesh.github.io/handbook/sde-coding/recursion-backtracking/calculator-misc.html)
- [Overview](https://abhinaavramesh.github.io/handbook/sde-coding/dynamic-programming/)
- [Climbing Stairs](https://abhinaavramesh.github.io/handbook/sde-coding/dynamic-programming/climbing-stairs.html)
- [House Robber](https://abhinaavramesh.github.io/handbook/sde-coding/dynamic-programming/house-robber.html)
- [Coin Change](https://abhinaavramesh.github.io/handbook/sde-coding/dynamic-programming/coin-change.html)
- [Knapsack](https://abhinaavramesh.github.io/handbook/sde-coding/dynamic-programming/knapsack.html)
- [Longest Increasing Subsequence](https://abhinaavramesh.github.io/handbook/sde-coding/dynamic-programming/longest-increasing-subsequence.html)
- [Longest Common Subsequence](https://abhinaavramesh.github.io/handbook/sde-coding/dynamic-programming/longest-common-subsequence.html)
- [Edit Distance](https://abhinaavramesh.github.io/handbook/sde-coding/dynamic-programming/edit-distance.html)
- [Word Break](https://abhinaavramesh.github.io/handbook/sde-coding/dynamic-programming/word-break.html)
- [Unique Paths](https://abhinaavramesh.github.io/handbook/sde-coding/dynamic-programming/unique-paths.html)
- [Minimum Path Sum](https://abhinaavramesh.github.io/handbook/sde-coding/dynamic-programming/minimum-path-sum.html)
- [Maximum Subarray](https://abhinaavramesh.github.io/handbook/sde-coding/dynamic-programming/maximum-subarray.html)
- [Decode Ways](https://abhinaavramesh.github.io/handbook/sde-coding/dynamic-programming/decode-ways.html)
- [Target Sum](https://abhinaavramesh.github.io/handbook/sde-coding/dynamic-programming/target-sum.html)
- [Partition Equal Subset](https://abhinaavramesh.github.io/handbook/sde-coding/dynamic-programming/partition-equal-subset.html)
- [Matrix Chain](https://abhinaavramesh.github.io/handbook/sde-coding/dynamic-programming/matrix-chain.html)
- [Burst Balloons](https://abhinaavramesh.github.io/handbook/sde-coding/dynamic-programming/burst-balloons.html)
- [Regex Matching](https://abhinaavramesh.github.io/handbook/sde-coding/dynamic-programming/regex-matching.html)
- [Wildcard Matching](https://abhinaavramesh.github.io/handbook/sde-coding/dynamic-programming/wildcard-matching.html)
- [Climbing & Knapsack](https://abhinaavramesh.github.io/handbook/sde-coding/dynamic-programming/climbing-knapsack.html)
- [Coin Change & Paths](https://abhinaavramesh.github.io/handbook/sde-coding/dynamic-programming/coin-change-paths.html)

## ML Fundamentals

- [Overview](https://abhinaavramesh.github.io/handbook/ml-fundamentals/)
- [How to Answer](https://abhinaavramesh.github.io/handbook/ml-fundamentals/concepts-overview.html)
- [Linear Regression](https://abhinaavramesh.github.io/handbook/ml-fundamentals/linear-regression.html)
- [Logistic Regression](https://abhinaavramesh.github.io/handbook/ml-fundamentals/logistic-regression.html)
- [Decision Trees](https://abhinaavramesh.github.io/handbook/ml-fundamentals/decision-trees.html)
- [SVM](https://abhinaavramesh.github.io/handbook/ml-fundamentals/svm.html)
- [KNN](https://abhinaavramesh.github.io/handbook/ml-fundamentals/knn.html)
- [Clustering](https://abhinaavramesh.github.io/handbook/ml-fundamentals/clustering.html)
- [Overview](https://abhinaavramesh.github.io/handbook/ml-fundamentals/neural-networks/)
- [Perceptrons & MLPs](https://abhinaavramesh.github.io/handbook/ml-fundamentals/neural-networks/01-perceptrons-mlps.html)
- [Activation Functions](https://abhinaavramesh.github.io/handbook/ml-fundamentals/neural-networks/02-activation-functions.html)
- [Backpropagation](https://abhinaavramesh.github.io/handbook/ml-fundamentals/neural-networks/03-backpropagation.html)
- [Weight Initialization](https://abhinaavramesh.github.io/handbook/ml-fundamentals/neural-networks/04-weight-initialization.html)
- [Normalization](https://abhinaavramesh.github.io/handbook/ml-fundamentals/neural-networks/05-normalization.html)
- [CNNs](https://abhinaavramesh.github.io/handbook/ml-fundamentals/neural-networks/06-cnns.html)
- [RNN, LSTM, GRU](https://abhinaavramesh.github.io/handbook/ml-fundamentals/neural-networks/07-rnns-lstm-gru.html)
- [Autoencoders & VAE](https://abhinaavramesh.github.io/handbook/ml-fundamentals/neural-networks/08-autoencoders-vae.html)
- [GANs](https://abhinaavramesh.github.io/handbook/ml-fundamentals/neural-networks/09-gans.html)
- [Optimizers](https://abhinaavramesh.github.io/handbook/ml-fundamentals/neural-networks/10-optimizers.html)
- [Regularization](https://abhinaavramesh.github.io/handbook/ml-fundamentals/neural-networks/11-regularization.html)
- [Gradient Problems](https://abhinaavramesh.github.io/handbook/ml-fundamentals/neural-networks/12-gradient-problems.html)
- [Overview](https://abhinaavramesh.github.io/handbook/ml-fundamentals/transformers/)
- [Attention Fundamentals](https://abhinaavramesh.github.io/handbook/ml-fundamentals/transformers/attention-fundamentals.html)
- [Self-Attention Mechanics](https://abhinaavramesh.github.io/handbook/ml-fundamentals/transformers/self-attention-mechanics.html)
- [Multi-Head Attention](https://abhinaavramesh.github.io/handbook/ml-fundamentals/transformers/multi-head-attention.html)
- [Positional Encoding](https://abhinaavramesh.github.io/handbook/ml-fundamentals/transformers/positional-encoding.html)
- [Encoder Architecture](https://abhinaavramesh.github.io/handbook/ml-fundamentals/transformers/encoder-architecture.html)
- [Decoder Architecture](https://abhinaavramesh.github.io/handbook/ml-fundamentals/transformers/decoder-architecture.html)
- [Training & Optimization](https://abhinaavramesh.github.io/handbook/ml-fundamentals/transformers/training-optimization.html)
- [Model Variants & Scaling](https://abhinaavramesh.github.io/handbook/ml-fundamentals/transformers/model-variants.html)
- [Practical Applications](https://abhinaavramesh.github.io/handbook/ml-fundamentals/transformers/practical-applications.html)
- [Interview Questions](https://abhinaavramesh.github.io/handbook/ml-fundamentals/transformers/interview-questions.html)
- [Overview](https://abhinaavramesh.github.io/handbook/ml-fundamentals/reinforcement-learning/)
- [MDP Foundations](https://abhinaavramesh.github.io/handbook/ml-fundamentals/reinforcement-learning/mdp-foundations.html)
- [Value Functions](https://abhinaavramesh.github.io/handbook/ml-fundamentals/reinforcement-learning/value-functions.html)
- [Exploration vs Exploitation](https://abhinaavramesh.github.io/handbook/ml-fundamentals/reinforcement-learning/exploration-exploitation.html)
- [TD Learning & Q-Learning](https://abhinaavramesh.github.io/handbook/ml-fundamentals/reinforcement-learning/temporal-difference.html)
- [Policy Gradients](https://abhinaavramesh.github.io/handbook/ml-fundamentals/reinforcement-learning/policy-gradients.html)
- [Actor-Critic Methods](https://abhinaavramesh.github.io/handbook/ml-fundamentals/reinforcement-learning/actor-critic.html)
- [Deep RL (DQN)](https://abhinaavramesh.github.io/handbook/ml-fundamentals/reinforcement-learning/deep-rl.html)
- [PPO & Modern Methods](https://abhinaavramesh.github.io/handbook/ml-fundamentals/reinforcement-learning/ppo-modern-methods.html)
- [RLHF & Alignment](https://abhinaavramesh.github.io/handbook/ml-fundamentals/reinforcement-learning/rlhf-alignment.html)
- [Advanced Topics](https://abhinaavramesh.github.io/handbook/ml-fundamentals/reinforcement-learning/advanced-topics.html)
- [Model Evaluation](https://abhinaavramesh.github.io/handbook/ml-fundamentals/model-evaluation.html)
- [FAQ Overview](https://abhinaavramesh.github.io/handbook/ml-fundamentals/interview-faq/)
- [Bias-Variance Tradeoff](https://abhinaavramesh.github.io/handbook/ml-fundamentals/interview-faq/core-concepts/bias-variance.html)
- [Regularization (L1/L2)](https://abhinaavramesh.github.io/handbook/ml-fundamentals/interview-faq/core-concepts/regularization.html)
- [Gradient Descent](https://abhinaavramesh.github.io/handbook/ml-fundamentals/interview-faq/optimization/gradient-descent.html)
- [Cross-Validation](https://abhinaavramesh.github.io/handbook/ml-fundamentals/interview-faq/optimization/cross-validation.html)
- [Ensemble Methods](https://abhinaavramesh.github.io/handbook/ml-fundamentals/interview-faq/models/ensemble-methods.html)
- [Hypothesis Testing](https://abhinaavramesh.github.io/handbook/ml-fundamentals/interview-faq/statistics/hypothesis-testing.html)
- [Overfitting & Underfitting](https://abhinaavramesh.github.io/handbook/ml-fundamentals/interview-faq/overfitting-underfitting.html)
- [Class Imbalance](https://abhinaavramesh.github.io/handbook/ml-fundamentals/interview-faq/class-imbalance.html)
- [Feature Engineering](https://abhinaavramesh.github.io/handbook/ml-fundamentals/interview-faq/feature-engineering.html)
- [Hyperparameter Tuning](https://abhinaavramesh.github.io/handbook/ml-fundamentals/interview-faq/hyperparameter-tuning.html)
- [Evaluation Metrics](https://abhinaavramesh.github.io/handbook/ml-fundamentals/interview-faq/evaluation-metrics.html)
- [Probability & Bayes](https://abhinaavramesh.github.io/handbook/ml-fundamentals/interview-faq/probability-bayes.html)
- [Vanishing Gradients](https://abhinaavramesh.github.io/handbook/ml-fundamentals/interview-faq/vanishing-gradients.html)
- [Transfer Learning](https://abhinaavramesh.github.io/handbook/ml-fundamentals/interview-faq/transfer-learning.html)
- [Model Drift](https://abhinaavramesh.github.io/handbook/ml-fundamentals/interview-faq/model-drift.html)
- [Interpretability (SHAP/LIME)](https://abhinaavramesh.github.io/handbook/ml-fundamentals/interview-faq/interpretability.html)

## GenAI Engineering

- [Overview](https://abhinaavramesh.github.io/handbook/genai/)
- [Overview](https://abhinaavramesh.github.io/handbook/genai/llm-foundations/)
- [How LLMs Work](https://abhinaavramesh.github.io/handbook/genai/llm-foundations/how-llms-work.html)
- [Tokenization Deep Dive](https://abhinaavramesh.github.io/handbook/genai/llm-foundations/tokenization-deep-dive.html)
- [Scaling Laws](https://abhinaavramesh.github.io/handbook/genai/llm-foundations/scaling-laws.html)
- [Model Families](https://abhinaavramesh.github.io/handbook/genai/llm-foundations/model-families.html)
- [Context & Memory](https://abhinaavramesh.github.io/handbook/genai/llm-foundations/context-and-memory.html)
- [Inference Optimization](https://abhinaavramesh.github.io/handbook/genai/llm-foundations/inference-optimization.html)
- [Overview](https://abhinaavramesh.github.io/handbook/genai/prompt-engineering/)
- [Prompt Anatomy](https://abhinaavramesh.github.io/handbook/genai/prompt-engineering/prompt-anatomy.html)
- [Few-Shot Learning](https://abhinaavramesh.github.io/handbook/genai/prompt-engineering/few-shot-learning.html)
- [Chain-of-Thought](https://abhinaavramesh.github.io/handbook/genai/prompt-engineering/chain-of-thought.html)
- [Advanced Techniques](https://abhinaavramesh.github.io/handbook/genai/prompt-engineering/advanced-techniques.html)
- [Prompt Optimization](https://abhinaavramesh.github.io/handbook/genai/prompt-engineering/prompt-optimization.html)
- [Prompt Security](https://abhinaavramesh.github.io/handbook/genai/prompt-engineering/prompt-security.html)
- [Prompt Evaluation](https://abhinaavramesh.github.io/handbook/genai/prompt-engineering/prompt-evaluation.html)
- [Overview](https://abhinaavramesh.github.io/handbook/genai/rag-systems/)
- [RAG Architecture](https://abhinaavramesh.github.io/handbook/genai/rag-systems/rag-architecture.html)
- [Embedding Models](https://abhinaavramesh.github.io/handbook/genai/rag-systems/embedding-models.html)
- [Vector Databases](https://abhinaavramesh.github.io/handbook/genai/rag-systems/vector-databases.html)
- [Chunking Strategies](https://abhinaavramesh.github.io/handbook/genai/rag-systems/chunking-strategies.html)
- [Retrieval Optimization](https://abhinaavramesh.github.io/handbook/genai/rag-systems/retrieval-optimization.html)
- [Advanced RAG Patterns](https://abhinaavramesh.github.io/handbook/genai/rag-systems/advanced-rag-patterns.html)
- [RAG Evaluation](https://abhinaavramesh.github.io/handbook/genai/rag-systems/rag-evaluation.html)
- [Overview](https://abhinaavramesh.github.io/handbook/genai/fine-tuning/)
- [When to Fine-Tune](https://abhinaavramesh.github.io/handbook/genai/fine-tuning/when-to-fine-tune.html)
- [Full Fine-Tuning](https://abhinaavramesh.github.io/handbook/genai/fine-tuning/full-fine-tuning.html)
- [PEFT Methods](https://abhinaavramesh.github.io/handbook/genai/fine-tuning/peft-methods.html)
- [Instruction Tuning](https://abhinaavramesh.github.io/handbook/genai/fine-tuning/instruction-tuning.html)
- [RLHF & DPO](https://abhinaavramesh.github.io/handbook/genai/fine-tuning/rlhf-dpo.html)
- [Data Preparation](https://abhinaavramesh.github.io/handbook/genai/fine-tuning/data-preparation.html)
- [Fine-Tuning Evaluation](https://abhinaavramesh.github.io/handbook/genai/fine-tuning/fine-tuning-evaluation.html)
- [Overview](https://abhinaavramesh.github.io/handbook/genai/agents-and-tools/)
- [Agent Architectures](https://abhinaavramesh.github.io/handbook/genai/agents-and-tools/agent-architectures.html)
- [Function Calling](https://abhinaavramesh.github.io/handbook/genai/agents-and-tools/function-calling.html)
- [Multi-Agent Systems](https://abhinaavramesh.github.io/handbook/genai/agents-and-tools/multi-agent-systems.html)
- [Memory & State](https://abhinaavramesh.github.io/handbook/genai/agents-and-tools/memory-and-state.html)
- [Agent Frameworks](https://abhinaavramesh.github.io/handbook/genai/agents-and-tools/agent-frameworks.html)
- [Agent Evaluation](https://abhinaavramesh.github.io/handbook/genai/agents-and-tools/agent-evaluation.html)
- [Overview](https://abhinaavramesh.github.io/handbook/genai/evaluation/)
- [Evaluation Taxonomy](https://abhinaavramesh.github.io/handbook/genai/evaluation/evaluation-taxonomy.html)
- [Automated Metrics](https://abhinaavramesh.github.io/handbook/genai/evaluation/automated-metrics.html)
- [LLM-as-Judge](https://abhinaavramesh.github.io/handbook/genai/evaluation/llm-as-judge.html)
- [Human Evaluation](https://abhinaavramesh.github.io/handbook/genai/evaluation/human-evaluation.html)
- [Hallucination Detection](https://abhinaavramesh.github.io/handbook/genai/evaluation/hallucination-detection.html)
- [Benchmarks](https://abhinaavramesh.github.io/handbook/genai/evaluation/benchmarks.html)
- [Overview](https://abhinaavramesh.github.io/handbook/genai/safety-and-alignment/)
- [Safety Fundamentals](https://abhinaavramesh.github.io/handbook/genai/safety-and-alignment/safety-fundamentals.html)
- [Content Filtering](https://abhinaavramesh.github.io/handbook/genai/safety-and-alignment/content-filtering.html)
- [Guardrails](https://abhinaavramesh.github.io/handbook/genai/safety-and-alignment/guardrails.html)
- [Red Teaming](https://abhinaavramesh.github.io/handbook/genai/safety-and-alignment/red-teaming.html)
- [Constitutional AI](https://abhinaavramesh.github.io/handbook/genai/safety-and-alignment/constitutional-ai.html)
- [Responsible AI](https://abhinaavramesh.github.io/handbook/genai/safety-and-alignment/responsible-ai.html)
- [Overview](https://abhinaavramesh.github.io/handbook/genai/llmops/)
- [Serving Infrastructure](https://abhinaavramesh.github.io/handbook/genai/llmops/serving-infrastructure.html)
- [Cost Optimization](https://abhinaavramesh.github.io/handbook/genai/llmops/cost-optimization.html)
- [Latency Optimization](https://abhinaavramesh.github.io/handbook/genai/llmops/latency-optimization.html)
- [Caching Strategies](https://abhinaavramesh.github.io/handbook/genai/llmops/caching-strategies.html)
- [Monitoring](https://abhinaavramesh.github.io/handbook/genai/llmops/monitoring.html)
- [Scaling Patterns](https://abhinaavramesh.github.io/handbook/genai/llmops/scaling-patterns.html)
- [Overview](https://abhinaavramesh.github.io/handbook/genai/multimodal/)
- [Vision-Language Models](https://abhinaavramesh.github.io/handbook/genai/multimodal/vision-language-models.html)
- [Image Generation](https://abhinaavramesh.github.io/handbook/genai/multimodal/image-generation.html)
- [Audio Models](https://abhinaavramesh.github.io/handbook/genai/multimodal/audio-models.html)
- [Video Understanding](https://abhinaavramesh.github.io/handbook/genai/multimodal/video-understanding.html)
- [Multimodal RAG](https://abhinaavramesh.github.io/handbook/genai/multimodal/multimodal-rag.html)
- [Overview](https://abhinaavramesh.github.io/handbook/genai/system-design/)
- [Design Framework](https://abhinaavramesh.github.io/handbook/genai/system-design/design-framework.html)
- [Chatbot Design](https://abhinaavramesh.github.io/handbook/genai/system-design/chatbot-design.html)
- [Enterprise RAG](https://abhinaavramesh.github.io/handbook/genai/system-design/enterprise-rag.html)
- [Code Assistant](https://abhinaavramesh.github.io/handbook/genai/system-design/code-assistant.html)
- [Content Pipeline](https://abhinaavramesh.github.io/handbook/genai/system-design/content-pipeline.html)
- [Interview Questions](https://abhinaavramesh.github.io/handbook/genai/system-design/interview-questions.html)

## ML Coding (From Scratch)

- [Overview](https://abhinaavramesh.github.io/handbook/ml-coding/)
- [Approach & Patterns](https://abhinaavramesh.github.io/handbook/ml-coding/coding-overview.html)
- [Quick Reference](https://abhinaavramesh.github.io/handbook/ml-coding/coding-reference.html)
- [Linear Regression](https://abhinaavramesh.github.io/handbook/ml-coding/linear-regression-implementation.html)
- [Logistic Regression](https://abhinaavramesh.github.io/handbook/ml-coding/logistic-regression-implementation.html)
- [KNN](https://abhinaavramesh.github.io/handbook/ml-coding/knn-implementation.html)
- [K-Means](https://abhinaavramesh.github.io/handbook/ml-coding/kmeans-implementation.html)
- [Decision Tree](https://abhinaavramesh.github.io/handbook/ml-coding/decision-tree-implementation.html)
- [Random Forest](https://abhinaavramesh.github.io/handbook/ml-coding/random-forest.html)
- [Naive Bayes](https://abhinaavramesh.github.io/handbook/ml-coding/naive-bayes.html)
- [SVM](https://abhinaavramesh.github.io/handbook/ml-coding/svm-implementation.html)
- [PCA](https://abhinaavramesh.github.io/handbook/ml-coding/pca-implementation.html)
- [Neural Network MLP](https://abhinaavramesh.github.io/handbook/ml-coding/neural-network-mlp.html)
- [Softmax & Cross-Entropy](https://abhinaavramesh.github.io/handbook/ml-coding/softmax-crossentropy.html)
- [Batch Norm & Dropout](https://abhinaavramesh.github.io/handbook/ml-coding/batch-norm-dropout.html)
- [Self-Attention](https://abhinaavramesh.github.io/handbook/ml-coding/self-attention.html)
- [2D Convolution](https://abhinaavramesh.github.io/handbook/ml-coding/cnn-filter.html)
- [Feature Scaling](https://abhinaavramesh.github.io/handbook/ml-coding/feature-scaling.html)
- [Practical Problems](https://abhinaavramesh.github.io/handbook/ml-coding/practical-problems.html)

## ML System Design

- [Overview](https://abhinaavramesh.github.io/handbook/ml-design/)
- [ML Domain Round](https://abhinaavramesh.github.io/handbook/ml-design/ml-domain-round.html)
- [Real Interview Questions](https://abhinaavramesh.github.io/handbook/ml-design/real-questions.html)
- [Design Framework](https://abhinaavramesh.github.io/handbook/ml-design/framework.html)
- [Key Phrases](https://abhinaavramesh.github.io/handbook/ml-design/key-phrases.html)
- [Experience Mapping](https://abhinaavramesh.github.io/handbook/ml-design/experience-mapping.html)

## Behavioural Interviews

- [Overview](https://abhinaavramesh.github.io/handbook/behavioural/)
- [STAR Framework](https://abhinaavramesh.github.io/handbook/behavioural/star-framework.html)
- [Quick Reference](https://abhinaavramesh.github.io/handbook/behavioural/quick-reference.html)
- [Google](https://abhinaavramesh.github.io/handbook/behavioural/companies/google.html)
- [Amazon](https://abhinaavramesh.github.io/handbook/behavioural/companies/amazon.html)
- [Meta](https://abhinaavramesh.github.io/handbook/behavioural/companies/meta.html)
- [Microsoft](https://abhinaavramesh.github.io/handbook/behavioural/companies/microsoft.html)
- [AI Labs](https://abhinaavramesh.github.io/handbook/behavioural/companies/ai-labs.html)
- [Apple, Netflix, Stripe](https://abhinaavramesh.github.io/handbook/behavioural/companies/apple-netflix-stripe.html)
- [Common Questions](https://abhinaavramesh.github.io/handbook/behavioural/common-questions.html)
- [Questions Bank (148)](https://abhinaavramesh.github.io/handbook/behavioural/questions-bank.html)
- [Story Templates](https://abhinaavramesh.github.io/handbook/behavioural/story-templates.html)

## /guides/

- [Prep with AI](https://abhinaavramesh.github.io/handbook/guides/prep-with-ai.html)

## /resources/

- [ML Interview Anki Deck](https://abhinaavramesh.github.io/handbook/resources/anki-deck.html)