Topic: machine-learning

Machine learning is a method of data analysis that automates analytical model building. Using algorithms that iteratively learn from data, machine learning allows computers to find hidden insights without being explicitly programmed where to look.

tensorflow

65703 0,71,92,238,140,0,217,0

Computation using data flow graphs for scalable machine learning

scikit-learn

18697 0,15,63,53,0,30,0,42

scikit-learn: machine learning in Python

serverless

16596 0,9,93,56,0,39,0,35

Serverless Framework – Build web, mobile and IoT applications with serverless architectures using AWS Lambda, Azure Functions, Google CloudFunctions & more! –

serverless

16596 0,9,93,56,0,39,0,35

Serverless Framework – Build web, mobile and IoT applications with serverless architectures using AWS Lambda, Azure Functions, Google CloudFunctions & more! –

keras

15801 0,27,0,47,28,63,0,16

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano.

awesome-selfhosted

15696 0,18,72,83,12,30,0,42

This is a list of Free Software network services and web applications which can be hosted locally. Selfhosting is the process of locally hosting and managing applications instead of renting from SaaS providers.

machine-learning-for-software-engineers

14887 0,358,37,57

A complete daily plan for studying to become a machine learning engineer.

awesome-deep-learning-papers

11365 0,5,20,24,14,0,28,8

The most cited deep learning papers

TensorFlow-Examples

11306 0,15,0,22,8,28,0,12

TensorFlow Tutorial and Examples for beginners

mxnet

9735 0,14,0,31,13,25,0,16

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

cs-video-courses

9464

List of Computer Science courses with video lectures.

data-science-ipython-notebooks

9101 0,2,9,10,14,0,12,0

Recently updated with 50 new notebooks! 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