Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.
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Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
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.
One has no future if one couldn't teach themself.
Python code for "Probabilistic Machine learning" book by Kevin Murphy
T81-558: Keras - Applications of Deep Neural Networks @Washington University in St. Louis
Translated"PyTorch Practical Tutorial" (Second Edition): whether you are starting from zero, working on CV, NLP, or LLM project applications, or moving on to advanced engineering deployment, it's all here. We believe that with the help of this book, readers will be able to master the use of PyTorch with ease and become an excellent deep learning engineer.
Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
Repo for AI Agents The Definitive Guide
A computer vision closed-loop learning platform where code can be run interactively online. 学习闭环《计算机视觉实战演练:算法与应用》中文电子书、源码、读者交流社区(持续更新中 ...) 📘 在线电子书 https://charmve.github.io/computer-vision-in-action/ 👇项目主页
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BER
Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.