rajeshg2017,github

10-steps-to-become-a-data-scientist

In this repository, we want to review 10 skills as data scientist: Machine Learning, Deep Learning, Data Cleaning, EDA, Learn Python, Learn python packages such as Numpy, Pandas, Seaborn, Matplotlib, Plotly, Tensorfolw, Theano...., Linear Algebra, Big Data, Analysis Tools and solve real problem for instance predict house prices.

100-days-of-ml-code

100 Days of ML Coding

9stepsawesome

The exercises/samples repo for bit.ly/9stepsawesome presentation

a-to-z-resources-for-students

✅ Curated list of resources for college students

adv_fin_ml_exercises

Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado]

aif360

A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.

amazon-sagemaker-examples

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

ansible-examples

A few starter examples of ansible playbooks, to show features and how they work together. See http://galaxy.ansible.com for example roles from the Ansible community for deploying many popular applications.

ansible-for-devops

Ansible examples from Ansible for DevOps.

awesome-learn-datascience

:chart_with_upwards_trend: Curated list of resources to help you get started with Data Science

aws-cloudformation-master

Learn AWS CloudFormation for infrastructure as code (IaC)

aws-cloudformation-templates

A collection of useful CloudFormation templates

aws-devops-essential

In few hours, quickly learn how to effectively leverage various AWS services to improve developer productivity and reduce the overall time to market for new product capabilities.