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Accurately Locate Smartphones using Social Engineering
Information gathering framework for phone numbers
The compiled, clean (not run) Jupyter notebooks for Elegant SciPy
Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.
My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (2000+ slides) 我不间断更新的机器学习，概率模型和深度学习的讲义(2000+页)和视频链接
Algorithms and data structures in Kotlin.
AI Projects in PyTorch
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
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.
A collection of IPython notebooks covering various topics.
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials,…
Python code for common Machine Learning Algorithms
In This repository I made some simple to complex methods in machine learning. Here I try to build template style code.
An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code
The "Python Machine Learning (2nd edition)" book code repository and info resource
Slides and notebooks for my tutorial at PyData London 2018
Machine Learning with Text in scikit-learn
Python Data Science Handbook: full text in Jupyter Notebooks
Notebooks for "Python for Signal Processing" book
Notes on the Deep Learning book from Ian Goodfellow, Yoshua Bengio and Aaron Courville (2016)
TensorFlow Basic Tutorial Labs
Programming Assignments and Lectures for Stanford's CS 231: Convolutional Neural Networks for Visual Recognition
Advanced Statistical Computing at Vanderbilt University Medical Center's Department of Biostatistics