🌟 Comprehensive AI/ML Resources📚 🌟

🚀 A Complete AI/ML Repository with in-depth coverage of Math, Python, Machine Learning, Deep Learning, NLP, Computer Vision, LLMs, Agentic AI, MLOps, and End To End Projects 🚀

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📑 Table of Contents

Section	Description
01. Math for AI and ML	Math foundations for AI/ML like linear algebra, calculus, statistic and probability.
02. Python	Python fundamentals, data structures, libraries, and more.
03. Machine Learning	Core ML algorithms, models, techniques, and much more.
04. Deep Learning	Dive into ANN, CNN, RNN, LSTM, and more.
05. NLP	Natural Language Processing using ML and DL models, preprocessing techniques, tools in NLP, and more.
06. Computer Vision	Introduction to CV, Object detection, GANs, image segmentation, and OpenCV.
07. Generative AI & LLMs	Explore the world of Large Language Models and Generative AI.
08. Agentic AI	Dive deep into Agentic AI and Automation.
09. MLOps	Tools, courses, and resources for MLOps.
10. End-To-End Projects	Comprehensive end-to-end projects.

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01. Math for AI and ML 📐

1. Linear Algebra

   • Introduction, System of Equations, Matrix Operations, Eigenvalues & Eigenvectors, and more.

2. Calculus

   • Limits, Derivatives, Chain Rules, Partial Derivatives, etc.

3. Probability

   • Introduction to Probability, Bayes Theorem, Permutations, Probability Distribution, etc.

4. Statistics

   • Central Tendency, Hypothesis Testing, Plots (Box, QQ, Violin), and more.

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02. Python 🐍

1. Python Basics

   • Variables, Data Types, Lists, Functions, OOP, Error Handling, etc.

2. Data Structures & Algorithms

   • Arrays, Sorting, Searching, Linked Lists, Trees, Graphs, and more.

3. NumPy | Pandas | Matplotlib | Seaborn

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03. Machine Learning 🤖

📂 Topic	📑 Link to Notebook
1. Introduction To ML	🌐 Notebook
2. Linear Regression	🌐 Notebook
3. Logistic Regression	🌐 Notebook
4. Decision Tree	🌐 Notebook
5. SVM	🌐 Notebook
6. Naive Bayes	🌐 Notebook
7. KNN	🌐 Notebook
8. k-means Clustering	🌐 Notebook
9. Hierarchical Clustering	🌐 Notebook
10. DBSCAN	🌐 Notebook
11. PCA	🌐 Notebook
12. LDA	🌐 Notebook
13. Ensemble Learning	🌐 Notebook
14. Random Forest	🌐 Notebook
15. Gradient Boost	🌐 Notebook
16. XGBoost Regression	🌐 Notebook
17. XGBoost Classification	🌐 Notebook
18. Adaboost	🌐 Notebook
19. Regression Metrics	🌐 Notebook
20. Classification Metrics	🌐 Notebook
21. Lasso And Ridge Regression	🌐 Notebook
22. Hyperparameter Tuning & Cross Validation	🌐 Notebook
23. ML Project Life-cycle	🌐 Notebook

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04. Deep Learning 🧠

📂 Topic	📑 Link to Notebook
1. Introduction To DL	🌐 Notebook
2. ANN	🌐 Notebook
3. Activation Functions	🌐 Notebook
4. Loss Functions	🌐 Notebook
5. Optimization	🌐 Notebook
6. Vanishing Explodings	🌐 Notebook
7. Overfit And Uderfit	🌐 Notebook
8. CNN	🌐 Notebook
9. CNN Architectures	🌐 Notebook
10. RNN	🌐 Notebook
11. LSTM And GRU	🌐 Notebook
12. BRNN	🌐 Notebook
13. Tensorflow And PyTorch	🌐 Notebook

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05. Natural Language Processing (NLP) 💬

📂 Topic	📑 Link to Notebook
1. Introduction To NLP	🌐 Notebook
2. Word Embeddings	🌐 Notebook
3. Word2vec	🌐 Notebook
4. Seq2Seq	🌐 Notebook
5. Transformers	🌐 Notebook
6. DL Models In NLP	🌐 Notebook

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06. Computer Vision (CV) 👁️

📂 Topic	📑 Link to Notebook
1. Introduction To CV	🌐 Notebook
2. Object Detection	🌐 Notebook
3. OpenCV	🌐 Notebook
4. GAN	🌐 Notebook
5. Image Segmentation	🌐 Notebook

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07. Generative AI & LLMs 📝

📂 Topic	📑 Link to Notebook
1. Introduction to Generative AI & LLMs	🌐 Notebook
2. Retrieval-Augmented Generation (RAG)	🌐 Notebook
3. Revealing the training secret of DeepSeek	🌐 Notebook

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08. Agentic AI 🦾

📂 Topic	📑 Link to Notebook
1. Introduction to Agentic AI	🌐 Notebook

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09. MLOps Resources ⚙️

1. Github: Github |

2. Docker: Docker Tutorial for Beginners (TechWorld with Nana) | End To End Machine Learning Project Implementation With Dockers (Krish Naik)

3. MLFlow: MLflow in Machine Learning

4. CI/CD: GitHub Actions Tutorial (TechWorld with Nana) | GitHub Actions (glich.stream)

5. Kubernete: Kubernetes Tutorial for Beginners (TechWorld with Nana)

6. AWS: AWS Cloud Practitioner (Udemy)

MLOps Courses:

Platform	Links
⚙️ Coursera	MLOps Specialization
⚙️ Udemy	Machine Learning Specialty

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10. End-To-End Projects 🥷🏻

📂 Topic	📑 Link to Github Repository
1. End-To-End ML Project (Liver Disease)	🔗 Github
2. End-To-End NLP Project (Hate Speech Detection)	🔗 Github
3. End-To-End DL/Computer Vision Project (Medical Image Analysis)	🔗 Github
4. End-To-End LLM Project(Medical Chatbot)	🔗 Github
5. End-To-End RAG Project (Corrective RAG)	🔗 Github
6. End-To-End MLOps Project	🔗 Github

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Repository created and maintained by Fraidoon Omarzai

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