Course materials for: Introduction to Data Science and Programming

There are plenty of courses and tutorials that can help you learn machine learning from scratch but here in GitHub, I want to solve some Kaggle competitions as a comprehensive workflow with python packages. After reading, you can use this workflow to solve other real problems and use it as a template.

Atom notebook

Automagically remove trends from time-series data

Deliverable: This Jupyter notebook will help aspiring data scientists learn and practice the necessary python code needed for many data science projects.

A collection of code examples as well as presentations for training purposes

Code release for Hu et al. Segmentation from Natural Language Expressions. in ECCV, 2016

机器学习实战

Videos of deep learning optimizers moving on 3D problem-landscapes

自然语言处理NLP在中文文本上的一些应用，如文本分类、情感分析、命名实体识别等

This repository shows a sample example to build, manage and orchestrate Machine Learning workflows using Amazon Sagemaker and Apache Airflow.

Breast Cancer Classification using CNN and transfer learning

A community run, 5-day PyTorch Deep Learning Bootcamp

A lightweight book theme built off of the pydata sphinx theme

Book sample (AI Machine-learning Deep-learning)

Repository for reading Pascal VOC data in Python, rather than requiring MATLAB to read the XML files.

Distributed deep learning on Hadoop and Spark clusters.

Gamified tutorial for the QISKit quantum SDK