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Get up and running with Llama 3.2, Mistral, Gemma 2, and other large language models.
API service to get data from Transfermarkt
A resource for learning about Machine learning & Deep Learning
Describing CycleGAN (excerpt from CADL course on Kadenze, Inc.)
The aim is to understand which are the key factors for a certain level of credit risk to occur. In addition, some ML models capable to predict the credit risk level for a company in an year - given…
transcripts and captions for 3blue1brown videos
The official PyTorch implementation of Google's Gemma models
• Calculated the Capital Ratios,Risk Weighted Assets, Capital requirement over projected time horizon for both CCAR and CECL. • Created PD model using Time Series,Logistic regression,Random Forests…
Books related to Artificial Intelligence, Machine Learning, Deep Learning and Neural Networks
A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API
The simplest, fastest repository for training/finetuning medium-sized GPTs.
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.
All data sets required for the examples and exercises in the book "Forecasting: principles and practice" (3rd ed, 2020) by Rob J Hyndman and George Athanasopoulos <https://OTexts.org/fpp3/>. All pac…
Slides to accompany Forecasting: Principles and Practice, 3rd edition
Modern Computer Vision with PyTorch, published by Packt
Lab Materials for MIT 6.S191: Introduction to Deep Learning