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100-days-of-ml-code

100 Days of ML Coding

100daysofstatandmath

This repository contains code and supporting files for 100 days of statistics and mathematics series which I am running on LinkedIn

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ai-ml-dl

algorithms

C++ implementation of basic algorithms

aliphysics

ALICE Analysis Repository

amazon-sagemaker-examples

Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker

applied-ml

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

approachingalmost

Approaching (Almost) Any Machine Learning Problem

aureliengeron

“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.

automation-email

awesome-github-profile-readme

😎 A curated list of awesome GitHub Profile READMEs 📝

awesome-interview-questions

:octocat: A curated awesome list of lists of interview questions. Feel free to contribute! :mortar_board:

awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

aws-ml-guide

[Video]AWS Certified Machine Learning-Specialty (ML-S) Guide

brewereader

Machine learning and computer vision to count beer consumption

car-price-prediction

cloudformation-course

files for the cloudformation course

coding

Sample codes for practice

course_aws_certified_machine_learning

coursera-machine-learning-1

Coursera's Machine Learning by Andrew Ng

coursera-machine-learning-in-python

machine learning algorithms in python from scratch

coursera-stanford-ml-python

Coursera/Stanford Machine Learning course assignments in python

courseraml

I took Andrew Ng's Machine Learning course on Coursera and did the homework assigments... but, on my own in python because I love jupyter notebooks!

data-science--cheat-sheet

Cheat Sheets

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.

data-science-portfolio

A Portfolio of my Data Science Projects

data-structures-algorithms-python

This tutorial playlist covers data structures and algorithms in python. Every tutorial has theory behind data structure or an algorithm, BIG O Complexity analysis and exercises that you can practice on.

decision-trees-for-ml

Building Decision Trees From Scratch In Python

deep-learning-coursera

Deep Learning Specialization by Andrew Ng on Coursera.