aditya-bhat

aditya-bhat.github.io

aws-real-time-face-recognition-as-a-service

data-modeling-with-cassandra

document-clustering-and-visualization

CSE 573 - Semantic Web Mining

hmm-part-of-speech-tagger

Hidden Markov Model based Parts of Speech Tagger using the Pomegranate library.

machine-learning-case-studies

Case studies on various Machine Learning and Deep Learning Models.

machine-learning-engineering-for-production-mlops-specialization

This repository contains my notebooks/code for the Machine Learning Engineering for Production (MLOps) Specialization courses. This Specialization is offered by deeplearning.ai via Coursera.

mit-deep-learning-book-pdf

MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville

natural-language-processing-specialization

Offered by deeplearning.ai via Coursera. The course is taught by Younes Bensouda Mourri, Łukasz Kaiser, and Eddy Shyu.

nlp-in-practice

Starter code to solve real world text data problems. Includes: Gensim Word2Vec, phrase embeddings, Text Classification with Logistic Regression, word count with pyspark, simple text preprocessing, pre-trained embeddings and more.

numerical-linear-algebra

Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course

python-design-patterns

redshift-data-warehouse

A music streaming startup, Sparkify, has grown their user base and song database and want to move their processes and data onto the cloud. Their data resides in S3, in a directory of JSON logs on user activity on the app, as well as a directory with JSON metadata on the songs in their app. As their data engineer, you are tasked with building an ETL pipeline that extracts their data from S3, stages them in Redshift, and transforms data into a set of dimensional tables for their analytics team to continue finding insights in what songs their users are listening to. You'll be able to test your database and ETL pipeline by running queries given to you by the analytics team from Sparkify and compare your results with their expected results.

spark-and-python-for-big-data-with-pyspark

Spark and Python for Big Data with PySpark

stock-dashboard

summer2023-internships

Collection of Summer 2023 tech internships!

tensorflow-2.0-deep-learning-and-artificial-intelligence

Jupyter Notebooks for Tensorflow 2.0: Deep Learning and Artificial Intelligence

tensorflow-deep-learning

Notebooks on Deep Learning using TensorFlow2.x

tensorflow-examples

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