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Polish roadmap and add link-check tooling
Add clearer DSA placement in the main roadmap, improve DSA course navigation and practice links, fix several internal markdown anchors/paths, and introduce a reusable internal link checker under tools/.
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00-prerequisites/02-linear-algebra.md

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- [Matrix Operations](#matrix-operations)
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- [Solving Systems of Linear Equations](#solving-systems-of-linear-equations)
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- [Gaussian Elimination (Row Reduction)](#gaussian-elimination-row-reduction)
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- [Solving Ax = 0 (Homogeneous System)](#solving-ax--0-homogeneous-system)
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- [Solving Ax = b (Non-homogeneous System)](#solving-ax--b-non-homogeneous-system)
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- [Solving Ax = 0 (Homogeneous System)](#solving-ax-0-homogeneous-system)
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- [Solving Ax = b (Non-homogeneous System)](#solving-ax-b-non-homogeneous-system)
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- [Column Space and Nullspace](#column-space-and-nullspace)
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- [Column Space (Range)](#column-space-range)
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- [Nullspace (Kernel)](#nullspace-kernel)

README.md

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*Perfect for beginners • 26 Learning Modules • 23 Real-World Projects • Production-Ready Skills*
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[Get Started](#getting-started)[Learning Path](#learning-path)[Projects](#phase-8-projects)[Contribute](#contributing)
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[Get Started](#getting-started)[Learning Path](#learning-path)[Projects](#phase-9-projects)[Contribute](#contributing)
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</div>
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**Goal**: Master critical skills for real-world ML applications
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**Note**: These modules can be learned in parallel with other phases or integrated earlier in your learning journey:
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- **DSA (recommended for interviews)**: Follow the [DSA Course (Python)](resources/dsa_course_python.md) alongside these modules to build strong coding + problem-solving fundamentals
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- **SQL** can be learned after Phase 1 (Data Fundamentals) for better data access skills
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- **Imbalanced Data** is most useful after Phase 2 (Classification) when you encounter real-world datasets
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- **Model Explainability** is valuable after Phase 3 (Advanced ML) when working with complex models

resources/career_portfolio.md

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- **Tools**: Docker, Kubernetes, AWS, Git
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## Projects
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- [Project 1](link) - Description
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- [Project 2](link) - Description
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- **Project 1** - Description (add your GitHub repo link)
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- **Project 2** - Description (add your GitHub repo link)
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## Connect
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- LinkedIn: [link]

resources/data_science_cheatsheet.md

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- [NumPy](#numpy)
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- [Pandas](#pandas)
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- [Matplotlib & Seaborn](#matplotlib--seaborn)
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- [Matplotlib & Seaborn](#matplotlib-seaborn)
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- [Scikit-learn](#scikit-learn)
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- [PyTorch](#pytorch)
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- [TensorFlow/Keras](#tensorflowkeras)
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- [OpenCV](#opencv)
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- [Hyperparameter Tuning & Model Optimization](#hyperparameter-tuning--model-optimization)
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- [FastAPI & Web Development](#fastapi--web-development)
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- [Hyperparameter Tuning & Model Optimization](#hyperparameter-tuning-model-optimization)
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- [FastAPI & Web Development](#fastapi-web-development)
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- [File Operations](#file-operations)
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- [List & Dictionary Operations](#list--dictionary-operations)
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- [List & Dictionary Operations](#list-dictionary-operations)
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- [String Operations](#string-operations)
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- [Date & Time](#date--time)
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- [Date & Time](#date-time)
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- [Useful Functions](#useful-functions)
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resources/dsa_course_python.md

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- [Appendix B: Practice Plan (6-8 Weeks)](#appendix-b-practice-plan-6-8-weeks)
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- [Appendix C: Curated Problem Set](#appendix-c-curated-problem-set)
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**Quick navigation:** [Start](#1-introduction-to-dsa-python-for-problem-solving)[Patterns](#11-patterns-problem-solving)[Trees](#12-trees)[Graphs](#13-graphs)[Heaps](#14-heaps-and-priority-queues)[DP](#15-dynamic-programming)[Practice Plan](#appendix-b-practice-plan-6-8-weeks)[Problem Set](#appendix-c-curated-problem-set)
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## 1. Introduction to DSA & Python for Problem Solving
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See also: `resources/practice_platforms.md`.
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- Arrays: two-sum, best time to buy/sell stock, product except self
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- Strings: valid anagram, longest substring without repeating
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- Linked list: reverse list, detect cycle, merge two sorted lists
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- Stack: valid parentheses, daily temperatures, next greater element
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- Queue/deque: sliding window maximum
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- Binary search: first/last position, search insert, rotated array
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- Hashing: subarray sum equals k, top k frequent
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- Heaps: kth largest element, merge k sorted lists, meeting rooms II
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- DP: climbing stairs, house robber, coin change, LIS, unique paths, LCS
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- Trees: level order, max depth, validate BST, LCA
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- Graphs: number of islands, course schedule, shortest path in grid
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**How to use this list (book-style):**
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- Pick **one topic/week**, solve **8–15 problems**
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- Start with **Easy**, then do **Medium**
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- For each problem: write brute force → optimize → explain complexity
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**Note**: Problem difficulties are based on the platform’s labels.
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### Arrays
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- [Two Sum](https://leetcode.com/problems/two-sum/) — Easy
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- [Best Time to Buy and Sell Stock](https://leetcode.com/problems/best-time-to-buy-and-sell-stock/) — Easy
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- [Product of Array Except Self](https://leetcode.com/problems/product-of-array-except-self/) — Medium
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- [Maximum Subarray](https://leetcode.com/problems/maximum-subarray/) — Medium
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### Strings
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- [Valid Anagram](https://leetcode.com/problems/valid-anagram/) — Easy
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- [Longest Substring Without Repeating Characters](https://leetcode.com/problems/longest-substring-without-repeating-characters/) — Medium
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- [Group Anagrams](https://leetcode.com/problems/group-anagrams/) — Medium
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### Linked List
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- [Reverse Linked List](https://leetcode.com/problems/reverse-linked-list/) — Easy
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- [Linked List Cycle](https://leetcode.com/problems/linked-list-cycle/) — Easy
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- [Merge Two Sorted Lists](https://leetcode.com/problems/merge-two-sorted-lists/) — Easy
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### Stack
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- [Valid Parentheses](https://leetcode.com/problems/valid-parentheses/) — Easy
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- [Daily Temperatures](https://leetcode.com/problems/daily-temperatures/) — Medium
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- [Next Greater Element I](https://leetcode.com/problems/next-greater-element-i/) — Easy
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### Queue / Deque
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- [Sliding Window Maximum](https://leetcode.com/problems/sliding-window-maximum/) — Hard
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### Binary Search
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- [First and Last Position of Element in Sorted Array](https://leetcode.com/problems/find-first-and-last-position-of-element-in-sorted-array/) — Medium
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- [Search Insert Position](https://leetcode.com/problems/search-insert-position/) — Easy
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- [Search in Rotated Sorted Array](https://leetcode.com/problems/search-in-rotated-sorted-array/) — Medium
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### Hashing
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- [Subarray Sum Equals K](https://leetcode.com/problems/subarray-sum-equals-k/) — Medium
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- [Top K Frequent Elements](https://leetcode.com/problems/top-k-frequent-elements/) — Medium
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### Heaps / Priority Queue
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- [Kth Largest Element in an Array](https://leetcode.com/problems/kth-largest-element-in-an-array/) — Medium
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- [Minimum Cost to Connect Sticks](https://leetcode.com/problems/minimum-cost-to-connect-sticks/) — Medium
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- [Merge k Sorted Lists](https://leetcode.com/problems/merge-k-sorted-lists/) — Hard
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- [Find Median from Data Stream](https://leetcode.com/problems/find-median-from-data-stream/) — Hard
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### Dynamic Programming (DP)
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- [Climbing Stairs](https://leetcode.com/problems/climbing-stairs/) — Easy
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- [House Robber](https://leetcode.com/problems/house-robber/) — Medium
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- [Coin Change](https://leetcode.com/problems/coin-change/) — Medium
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- [Unique Paths](https://leetcode.com/problems/unique-paths/) — Medium
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- [Longest Increasing Subsequence](https://leetcode.com/problems/longest-increasing-subsequence/) — Medium
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- [Longest Common Subsequence](https://leetcode.com/problems/longest-common-subsequence/) — Medium
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### Trees
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- [Binary Tree Level Order Traversal](https://leetcode.com/problems/binary-tree-level-order-traversal/) — Medium
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- [Maximum Depth of Binary Tree](https://leetcode.com/problems/maximum-depth-of-binary-tree/) — Easy
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- [Validate Binary Search Tree](https://leetcode.com/problems/validate-binary-search-tree/) — Medium
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- [Lowest Common Ancestor of a Binary Tree](https://leetcode.com/problems/lowest-common-ancestor-of-a-binary-tree/) — Medium
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### Graphs
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- [Number of Islands](https://leetcode.com/problems/number-of-islands/) — Medium
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- [Course Schedule](https://leetcode.com/problems/course-schedule/) — Medium
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- [Shortest Path in Binary Matrix](https://leetcode.com/problems/shortest-path-in-binary-matrix/) — Medium
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- [Clone Graph](https://leetcode.com/problems/clone-graph/) — Medium
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resources/generative_ai_comprehensive_guide.md

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- [LangChain Tutorials](https://python.langchain.com/docs/get_started/introduction)
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- [RAG Guide](resources/rag_comprehensive_guide.md)
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- [AI Agents Guide](resources/ai_agents_guide.md)
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- [GenAI Production Deployment](resources/genai_production_deployment.md)
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- [RAG Guide](rag_comprehensive_guide.md)
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- [AI Agents Guide](ai_agents_guide.md)
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- [GenAI Production Deployment](genai_production_deployment.md)
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### Vector Database Resources
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resources/git_guide.md

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- [Getting Started](#getting-started)
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- [Basic Git Commands](#basic-git-commands)
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- [Working with Branches](#working-with-branches)
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- [Remote Repositories & GitHub](#remote-repositories--github)
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- [Remote Repositories & GitHub](#remote-repositories-github)
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- [Advanced Git Operations](#advanced-git-operations)
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- [Git Workflows](#git-workflows)
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- [Practice Exercises](#practice-exercises)
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- [Common Scenarios](#common-scenarios)
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- [GitHub-Specific Features](#github-specific-features)
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- [Resources & Documentation](#resources--documentation)
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- [Resources & Documentation](#resources-documentation)
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resources/interview_prep.md

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- [ML Concepts Questions](#ml-concepts-questions)
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- [Coding Challenges](#coding-challenges)
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- [System Design Questions](#system-design-questions)
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- [Statistics & Probability](#statistics--probability)
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- [Statistics & Probability](#statistics-probability)
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- [Behavioral Questions](#behavioral-questions)
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- [Project Walkthrough](#project-walkthrough)
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- [Preparation Strategy](#preparation-strategy)

resources/ml_glossary.md

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## J
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**Jaccard Similarity**
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- Measures similarity between two sets
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- Formula: \(|A ∩ B| / |A ∪ B|\)
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- Common use: evaluating overlap in recommendations, clustering, and NLP set-based features
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**K-Fold Cross-Validation**
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## Q
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**Quantization**
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- Compressing model weights/activations to lower precision (e.g., FP16, INT8)
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- Benefits: Faster inference and lower memory usage
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- Common in production deployment and edge/CPU serving
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## Y
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**YOLO (You Only Look Once)**
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- Real-time object detection model family
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- Predicts bounding boxes and class probabilities in one forward pass
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- Common use: computer vision deployment where latency matters
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## Z
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**Z-score (Standard Score)**
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- Number of standard deviations a value is from the mean
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- Formula: \((x - μ) / σ\)
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- Common use: outlier detection and feature standardization
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resources/ml_model_testing.md

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- [Unit Testing for ML](#unit-testing-for-ml)
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- [Testing Data Preprocessing](#testing-data-preprocessing-functions)
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- [Testing Model Training](#testing-model-training)
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- [Testing Predictions](#testing-predictions)
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- [Testing APIs](#testing-apis)

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