Auto_Jobs_Applier_AIHawk is a tool that automates the jobs application process. Utilizing artificial intelligence, it enables users to apply for multiple job offers in an automated and personalized…

A cheatsheet for basic best practice in R programming

Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.

Python for Algorithmic Trading Cookbook, published by Packt

A tool for extracting and analyzing a company's finances

Machine Learning in Finance: From Theory to Practice Book

Code for Vue Mastery's Intro to Vue 3 course:

Bayesian Data Analysis course at Aalto

Practical Data Privacy

Source code accompanying book: Data Science on the Google Cloud Platform, Valliappa Lakshmanan, O'Reilly 2017

Learn how to design, develop, deploy and iterate on production-grade ML applications.

Tackling Climate Change with Time Series Analysis and Forecasting

Interact privately with your documents using the power of GPT, 100% privately, no data leaks

Time series analysis in the `tidyverse`

A GPT-4 AI Tutor Prompt for customizable personalized learning experiences.

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

🔥Highlighting the top ML papers every week.

Caffe: a fast open framework for deep learning.

Lab Materials for MIT 6.S191: Introduction to Deep Learning

Densely Connected Convolutional Networks, In CVPR 2017 (Best Paper Award).

A MNIST-like fashion product database. Benchmark 👇

Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1

Developing Data Products Course from the Johns Hopkins Data Science Lab

Jupyter Notebook extension leveraging pandas DataFrames by integrating DataTables and ChartJS.

DenseNet Implementation in Keras with ImageNet Pretrained Models