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📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
Python solutions to solve practical business problems.
Maze Applied Reinforcement Learning Framework
Curated list of technical blogs on machine learning · AI/ML/DL/CV/NLP/MLOps
📌 Papers, guides, and mentor interviews on applying machine learning for ApplyingML.com—the ghost knowledge of machine learning.
Detecting cinema shot types using a ResNet-50
📚「@MaiweiAI」Studying papers in the fields of computer vision, NLP, and machine learning algorithms every week.
Mask R-CNN Model to detect the area of damage on a car. The rationale for such a model is that it can be used by insurance companies for faster processing of claims if users can upload pics and they can assess damage from them. This model can also be used by lenders if they are underwriting a car loan especially for a used car.
📚 Curated collection of engineering blogs detailing real-world applications of LLMs in solving specific business problems.
📚 Curated list of machine learning engineering blogs.
Machine learning Regression problem with easy understandable solutions
Unity's Privacy-Preserving Novel Human Body Model Trained Solely on Synthetic Data and Corresponding Dense Anthropometric Measurements
My Assignment Submission made during the course 📙
📚 Curated collection of blogs and papers on how different companies are using machine learning in production for better customer support.
A curated list of resources to deep dive into the intersection of applied machine learning and threat detection.
This Repo contains - Starter files, Coursework, Programming Assignments for the course --> Applied Machine Learning in Python, University of Michigan [COURSERA]
Dream prediction by using neural networks on EEG time series collected from sleeping humans.
A collection of awesome software, learning tutorials, theoretical resources, books and videos, best practices in applied cryptography.
This repository provides a comprehensive implementation of supervised machine learning models using PyTorch and Scikit-learn. It includes end-to-end workflows for both classification and regression tasks, covering data preprocessing, model training, evaluation, and comparison between traditional ML models