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artificial-intelligence-deep-learning-machine-learning-tutorials

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Automotives, Retail, Pharma, Medicine, Healthcare by Tarry Singh until at-least 2020 until he finishes his Ph.D. (which might end up being inter-stellar cosmic networks! Who knows! 😀)

big-data-facebook-posts-analyzer

This is the course project for Big data technologies. Analyzing streaming facebook posts data.

bike_share_project

leverage ML algorithms and s3, MongoDB, spark, AWS to predict Bay Area bike share daily demand

capstone

clustering-news-headlines

The project groups scrapped News headlines using NLTK, K-Means clustering and Hierarchical clustering using Ward Method.

cookbook

The Data Engineering Cookbook

coursera-inferential-statistics-with-duke-univ

HW solutions to Inferential Statistics course on Coursera taught by professors at Duke University

coursera-introduction-to-probability-and-data

Statistics with R Specialization by Duke University on Coursera.

developerfolio

Software Developer Portfolio Template that help you showcase your work and skills as a software developer ⚡️

insurance_claims_prediction

lending-club-visualization

Designed interactive visualization and provided analysis for Lending Club Loan data.

msds692

MSAN692 Data Acquisition

scraping-glassdoor-selenium

Jupyter Notebook from Selenium Tutorial: Scraping Glassdoor.com"

serverless-data-analytics

CloudFormation templates and scripts to setup the AWS services for the workshop, Athena & Redshift Spectrum queries

skillsnetwork

solutions

Solutions for projects.

statistics-for-data-science

Learning Statistics is one of the most Important step to get into the World of Data Science and Machine Learning. Statistics helps us to know data in a much better way and explains the behavior of the data based upon certain factors. It has many Elements which help us to understand the data better that includes Probability, Distributions, Descriptive Analysis, Inferential Analysis, Comparative Analysis, Chi-Square Test, T Test, Z test, AB Testing etc.

statistics-for-data-scientists

Code and data associated with the book "Statistics for Data Scientists: 50 Essential Concepts"

temp

training-data-analyst

Labs and demos for courses for GCP Training (http://cloud.google.com/training).

yelp-review-dataset