1191 Open source projects that are alternatives of or similar to python-machine-learning-book-2nd-edition

This repository contains Ipython notebooks and datasets for the data analytics youtube tutorials on The Semicolon.

Credit Risk analysis by using Python and ML

Wavelet scattering transforms in Python with GPU acceleration

My solutions for Assignments of CS231n: Convolutional Neural Networks for Visual Recognition

Tutorials on getting started with PyTorch and TorchText for sentiment analysis.

Open source guides/codes for mastering deep learning to deploying deep learning in production in PyTorch, Python, C++ and more.

For extensive instructor led learning

Курс "Введение в машинное обучение" (ВМК, МГУ имени М.В. Ломоносова)

Alternative approach for Adaptive Computation Time in TensorFlow

📓 deepleaning and cv notes.

Human activity recognition using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six categories (WALKING, WALKING_UPSTAIRS, WALKING_DOWNSTAIRS, SITTING, STANDING, LAYING).

Deep learning codes and projects using Python

iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs | Published in Springer Journal of Computational Visual Media, September 2020, Tsinghua University Press

Use AI to generate a optimized stock portfolio

AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP

Open Machine Learning Course

A collection of notebooks of my Machine Learning class written in python 3

Small Docker image with Python Machine Learning tools (~180MB) https://hub.docker.com/r/frolvlad/alpine-python-machinelearning/

Keras, PyTorch, and NumPy Implementations of Deep Learning Architectures for NLP

📚 Various cheatsheets in PDF

Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.

Source code of the model used in Tensorflow Speech Recognition Challenge (https://www.kaggle.com/c/tensorflow-speech-recognition-challenge). The solution ranked in top 5% in private leaderboard.

Machine Learning Containers for NVIDIA Jetson and JetPack-L4T

Sequence analyzing using Recurrent Neural Networks (RNN) based on Keras

Speaker Diarization is the problem of separating speakers in an audio. There could be any number of speakers and final result should state when speaker starts and ends. In this project, we analyze given audio file with 2 channels and 2 speakers (on separate channels).

A library for performing hyperparameter optimization

pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.

Use tensorflow's tf.scan to build vanilla, GRU and LSTM RNNs

Recurrent Neural Network and Long Short Term Memory (LSTM) with Connectionist Temporal Classification implemented in Theano. Includes a Toy training example.

A recurrent attention module consisting of an LSTM cell which can query its own past cell states by the means of windowed multi-head attention. The formulas are derived from the BN-LSTM and the Transformer Network. The LARNN cell with attention can be easily used inside a loop on the cell state, just like any other RNN. (LARNN)

Docker Start Guide with Python Development Environment

Pytorch、Scikit-learn实现多种分类方法，包括逻辑回归（Logistic Regression）、多层感知机（MLP）、支持向量机（SVM）、K近邻（KNN）、CNN、RNN，极简代码适合新手小白入门，附英文实验报告（ACM模板）

My workshop on machine learning using python language to implement different algorithms

PyTorch tutorial for learners

Alpine Container for Machine Learning

The book was written and tested with Python 3.5, though other Python versions (including Python 2.7) should work in nearly all cases.

notebooks with example for machine learning examples

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, AWS, and various command lines.

Parallel computing with task scheduling

A series of self-correcting challenges for practicing your Machine Learning and Deep Learning skills

Example PyMC3 project for performing Bayesian data analysis using a probabilistic programming approach to machine learning.

A tutorial on how to implement models for part-of-speech tagging using PyTorch and TorchText.

How to build RNNs and LSTMs from scratch with NumPy.

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

A Case Study Approach to Successful Data Science Projects Using Python, Pandas, and Scikit-Learn

This project seeks to utilize Deep Learning models, Long-Short Term Memory (LSTM) Neural Network algorithm, to predict stock prices.

Comparing Fixed and Adaptive Computation Time for Recurrent Neural Networks

🍊 📊 💡 Orange: Interactive data analysis

Probabilistic Dialogue Act Classification for the Switchboard Corpus using an LSTM model

Python Cheat Sheet NumPy, Matplotlib

도서 "[개정판] 파이썬 라이브러리를 활용한 머신 러닝"의 주피터 노트북과 코드입니다.

A variational implementation of classical and quantum annealing using recurrent neural networks for the purpose of solving optimization problems.

[AAAI 2020] Modeling Personality with Attentive Networks and Contextual Embeddings

datascienv is package that helps you to setup your environment in single line of code with all dependency and it is also include pyforest that provide single line of import all required ml libraries

[ICMLC 2018] A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection

Python library for Reservoir Computing using Echo State Networks

Study E-Book(ComputerVision DeepLearning MachineLearning Math NLP Python ReinforcementLearning)

도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.

PyTorch/Tensorflow solutions for Stanford's CS231n: "CNNs for Visual Recognition"

Data Science with Python