This is a repo with links to everything you'd ever want to learn about data engineering
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Python programs, usually short, of considerable difficulty, to perfect particular skills.
- python
- python-3
- programming
- practice
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable, and secure AI workflows from session setup to service orchestration.
- csharp
- java
- javascript
- mcp
Natural Language Processing Tutorial for Deep Learning Researchers
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
- computer-vision
- deep-learning
- drug-discovery
- forecasting
Dive into this repository, a comprehensive resource covering Data Structures, Algorithms, 450 DSA by Love Babbar, Striver DSA sheet, Apna College DSA Sheet, and FAANG Questions! 🚀 That's not all! We've got Technical Subjects like Operating Systems, DBMS, SQL, Computer Networks, and Object-Oriented Programming, all waiting for you.
- interview-questions
- dsa
- dbms
- sql
Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
- andrew-ng
- andrew-ng-machine-learning
- coursera
- coursera-assignment
Sutskever 30 implementations inspired by https://papercode.vercel.app/ | For Agents, use https://github.com/pageman/Sutskever-Agent | Polyglot / Multi-Backed version at https://github.com/pageman/sutskever-30-beyond-numpy
Technical resources for AI developers to build applications, agents, and systems using Oracle AI Database and OCI services
- artificial-intelligence
- generative-ai
- kubernetes
- kustomize
Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models
- deep-learning
- coursera
- coursera-assignment
- coursera-specialization
Plain python implementations of basic machine learning algorithms
- machine-learning
- logistic-regression
- ipynb
- machine-learning-algorithms
Handout for the tutorial "Creating publication-quality figures with matplotlib"
Data Hacking Project
IPython notebooks on Gilbert Strang's MIT course on linear algebra (18.06)
Mostly experiments based on "Advances in financial machine learning" book
💸 Papers and Code Implements for Quantitative-Trading
Comparing the performance of Stacked Ensemble Learning & machine learning algorithms like Random Forest, Decision Tree, Adaboost, Gradient Boost and XGBoost Classifier in Python for Stock Market Trend Prediction.