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100-days-of-ml-code

100 Days of ML Coding

algorithms-explanation

All Algorithms explained in simple English Language with example and links to their implementation in various programming languages and other required resources.

bigdl

BigDL: Distributed Deep Learning Library for Apache Spark

client_golang

Prometheus instrumentation library for Go applications

cntk

Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit

data-science-ipython-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 command lines.

deep-learning-book

Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"

deploying-machine-learning-models

Example Repo for the Udemy Course "Deployment of Machine Learning Models"

django-rest-framework

Web APIs for Django. 🎸

face_recognition

The world's simplest facial recognition api for Python and the command line

go

Algorithms Implemented in GoLang

ml_cheat_sheet

My notes and superstitions about common machine learning algorithms

mlsl

Intel(R) Machine Learning Scaling Library is a library providing an efficient implementation of communication patterns used in deep learning.

powerai-vision-model-validation

powerai-vision-object-detection

Use deep learning to create a model and a REST endpoint to allow your app to detect, locate and count your product on store shelves

pyprojects

python

All Algorithms implemented in Python

python-patterns

A collection of design patterns/idioms in Python

pytorch-cheatsheet

Check out improved:

rango

Random. Django. Rango. An introduction to using Python and Django to build a website.

spacy

💫 Industrial-strength Natural Language Processing (NLP) with Python and Cython

spark

Apache Spark

sqlmap

Automatic SQL injection and database takeover tool

tensorflow-examples

TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

visualize-data-with-python

A Jupyter notebook using some standard techniques for data science and data engineering to analyze data for the 2017 flooding in Houston, TX.