7428 Open source projects that are alternatives of or similar to 50 Days Of Ml

This is Andrew NG Coursera Handwritten Notes.

Data Science Best Practices with pandas

Introduction to pandas Treehouse course

Tutorial: Web scraping in Python with Beautiful Soup

This repository provides everything you need to get started with Python for (social science) research.

[tutorial]A functional, Data Science focused introduction to Python

Practice your pandas skills!

Jupyter notebook and datasets from the pandas Q&A video series

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

Powerful financial charting library based on R's Quantmod | http://py-quantmod.readthedocs.io/en/latest/

image processing codes to understand algorithm

A hands-on introduction to video technology: image, video, codec (av1, vp9, h265) and more (ffmpeg encoding).

Anomaly detection tutorial on univariate time series with an auto-encoder

Important paper implementations for Question Answering using PyTorch

Scenarios, tutorials and demos for Autonomous Driving

Deep Learning based Automatic Speech Recognition with attention for the Nvidia Jetson.

AI-related tutorials. Access any of them for free → https://towardsai.net/editorial

Repository to store sample python programs for python learning

Combining Psi4 and Numpy for education and development.

HandySpark - bringing pandas-like capabilities to Spark dataframes

Technical Analysis Library using Pandas and Numpy

Functionalities in Excel translated to Python

Tutorials for the Astropy Project

Training Diary

Visualizer for pandas data structures

Toolkit to obtain and preprocess german corpora, train models using word2vec (gensim) and evaluate them with generated testsets

Tutorial Sessions for SciPy Con 2019

Google2Csv a simple google scraper that saves the results on a csv/xlsx/jsonl file

공공데이터 분석

Implementation of Siamese Neural Networks built upon multihead attention mechanism for text semantic similarity task.

Performance analysis of predictive (alpha) stock factors

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

🐍 Learn Python and Pandas from the ground up

A short tutorial on Elmo training (Pre trained, Training on new data, Incremental training)

📚 Various cheatsheets in PDF

Learn applied deep learning from zero to deployment using TensorFlow 1.8+

INTERSPEECH 2019 Tutorial Materials

Traffic Sign Detection. Code for the paper entitled "Evaluation of deep neural networks for traffic sign detection systems".

🟣 Object detection of abstract shapes with neural networks

Archived - not answering issues

A blog which talks about machine learning, deep learning algorithms and the Math. and Machine learning algorithms written from scratch.

主要是爬虫与数据分析项目总结，外加建模与机器学习，模型的评估。

Material for the tutorial: "Deep Diving into GANs: from theory to production"

top 1% solution to toxic comment classification challenge on Kaggle.

The Los Angeles Times' independent tally of coronavirus cases in California.

How to use TensorFlow

This is a tutorial for PyTorch Geometric on the YooChoose dataset

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

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

pandas中文教程

All course materials for the Zero to Mastery Deep Learning with TensorFlow course.

Stable-Baselines tutorial for Journées Nationales de la Recherche en Robotique 2019

Learn OpenCV : C++ and Python Examples

Simple plotting library that wraps Matplotlib and integrated with DataFrames

A Python Matplotlib, Numpy library to manage wind data, draw windrose (also known as a polar rose plot), draw probability density function and fit Weibull distribution

A Simple and easy to use way to Visualise Embeddings!

Deep learning system course

从零基础开始机器学习之旅

Quick, visual, principled introduction to pytorch code through five colab notebooks.

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.