6233 Open source projects that are alternatives of or similar to Viz_torch_optim

Reinforcement learning with A* and a deep heuristic

Gemfield homework or libgemfield.so

Old source for jakevdp.github.io. New source at http://github.com/jakevdp/jakevdp.github.io-source

Computer Science SCHOOL resources

Templates for jupyter notebooks

Koç University deep learning framework.

Seaborn 学习笔记

Caffe implementation of Mobilenet-SSD face detector (NCS compatible)

Microscopy Image Cytometry Toolkit

BERT + Image Captioning

100+ python programming exercise problem discussed ,explained and solved in different ways

GANs in slanted land

Designing Deep neural network architectures using topologies from the world of Complex Networks/network Science

Material that I use for a variety of classes and tutorials

📓 A growing collection of Jupyter Notebooks written in Python, OCaml and Julia for science examples, algorithms, visualizations etc

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.

Kaggle Quora Questions Pairs Competition

Taking a pretrained GloVe model, and using it as a TensorFlow embedding weight layer **inside the GPU**. Therefore, you only need to send the index of the words through the GPU data transfer bus, reducing data transfer overhead.

This is the new version of the emergent neural network simulation software, written now in Go (golang)

Course materials for: Introduction to Data Science and Programming

VGG-19 deep learning model trained using ISCX 2012 IDS Dataset

《Python工具代码速查手册》是我们的python培训教材，主要面向数据分析方向。其中包含了python的常用总结性操作，使用jupyter notebook，利用markdown和script结果对常用操作进行总结，包括了使用方式和脚本。之所以使用notebook形式是可以方便大家编辑，方便大家形成自己的总结笔记。当然各位有更好的操作建议也欢迎向我们团队分享~

Introduction to manifold learning - mathematical theory and applied python examples (Multidimensional Scaling, Isomap, Locally Linear Embedding, Spectral Embedding/Laplacian Eigenmaps)

Notebooks de análises e projetos de Data Science em Python

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

This mathematics course is taught for the first year Ph.D. students of computer science and related areas @ZJU

Discovering Interpretable GAN Controls [NeurIPS 2020]

Bert-base NLP pipeline for Turkish, Ner, Sentiment Analysis, Question Answering etc.

Book sample (AI Machine-learning Deep-learning)

Python-based spatial data analysis and visualization of the GPS location data from my 2014 summer travels.

“Hands-On Machine Learning with Scikit-Learn and TensorFlow” Excerpt From: Aurélien Géron. “Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems.” iBooks.

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

Examples for Deep Learning/Feature Store/Spark/Flink/Hive/Kafka jobs and Jupyter notebooks on Hops

Convolutional Gaussian processes based on GPflow.

Building classifiers using cancer transcriptomes across 33 different cancer-types

CAUTION: This is not maintained anymore. Visit https://github.com/chainer-community/chainer-colab-notebook/

Local Light Field Synthesis (Pratul P. Srinivasan, Tongzhou Wang, Ashwin Sreelal, Ravi Ramamoorthi, Ren Ng ICCV 2017)

Tianchi medical AI competition [Season 1]: Lung nodules image segmentation of U-Net. U-Net训练基于卷积神经网络的肺结节分割器

Breast Cancer Classification using CNN and transfer learning

Generating Captions for images using Deep Learning

Материалы курса по компьютерной лингвистике Школы Лингвистики НИУ ВШЭ

scaffold of Apache Airflow executing Docker containers

机器学习实战

Python codes for low-rank tensor factorization, tensor completion, and tensor regression techniques.

A lightweight book theme built off of the pydata sphinx theme

COVID-19 workflows and datasets.

This is the code for "Simple Blockchain in 5 Minutes" By Siraj Raval on Youtube

Gamified tutorial for the QISKit quantum SDK

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

Automagically remove trends from time-series data

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