📚 Papers by organizations sharing their work on applied data science & machine learning.

Python solutions to solve practical business problems.

Detecting cinema shot types using a ResNet-50

Machine learning Regression problem with easy understandable solutions

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

📚「MaiweiAI」Studying papers in the fields of computer vision, NLP, and machine learning algorithms every week.

My Assignment Submission made during the course 📙

Dream prediction by using neural networks on EEG time series collected from sleeping humans.

State-Of-The-Art Transformer Models

Applied machine learning coursera materials

Predicting opioid misuse using the National Survey on Drug Use and Health.

Capstone Project - Starbucks Challenge

Applied ML Algorithms On Amazon Fine Food Reviews.

Courses I have completed in Coursera

This project contains the code to perform a task of Particle identification (PID) in Astrophysics, comparing Deep Learning and Classical Machine Learning approaches. Data are provided by Agile team (http://agile.rm.iasf.cnr.it/) and the goal of the analysis is to provide a Statistical model which is able to distinguish gamma-ray photon for background particles.

A curated list of resources to deep dive into the intersection of applied machine learning and threat detection.

This repo has all the files that I used during the studies of ML and DS

Applied Machine Learning in Python

Metis Data Science Bootcamp : Project Directory

Machine Learning and Deep Learning in Bioinformatics - Master's thesis repository

Applied Machine Learning Online Course Solutions | Category: AI & Machine Learning

Applied DBSCAN | Columbia GSAPP

An approach to the agile desing and implementation of a data strategy in businesses

Summer is the best season in the real estate market and housing prices vary based on a number of features. Data from 2 such Summers is taken about the Kings County Housing Prices. Two Jupyter Notebooks depicting the various Regression models is used to depict how the number of bedrooms, waterfront location, total area in square feet, etc. affect the housing prices. Machine Learning with Python is used throughout the course of the project. Jupyter Notebooks give complete detail of implementation.

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It includes all the assignments of Data Science Specialization Course which contains Introduction to Data Science with Python, Plotting Charting & Representation using Python, Applied ML in Python, Social Network Analysis with Python, Text Mining with Python etc.

Applied Statistical Learning, A/B testing with Marketing Analytics, Data Analytics for Business Intelligence

Web-App of a Content Based Movie Recommender System using Flask

Machine Learning with Python 3