hyperparameter-tuning

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

The AI Compute Platform for frontier teams. SkyPilot turns fragmented AI compute into one AI supercomputer, so frontier AI teams build custom intelligence faster.

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.

A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.

Sequential model-based optimization with a `scipy.optimize` interface

Automated Machine Learning on Kubernetes

Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.

A collection of 100+ pre-trained RL agents using Stable Baselines, training and hyperparameter optimization included.

Programming assignments and lecture notes of the Deep Learning Specialization taught by Andrew Ng and offered by deeplearning.ai on Coursera.

Implementation of Logistic Regression, MLP, CNN, RNN & LSTM from scratch in python. Training of deep learning models for image classification, object detection, and sequence processing (including transformers implementation) in TensorFlow.

This repo contains my work & The code base for this Deep Learning Specialization offered by deeplearning.AI

Code and supplementary materials for the research paper titled 'Advancing Geological Image Segmentation: Deep Learning Approaches for Rock Type Identification and Classification', published in Applied Computing and Geosciences (Elsevier).

A repo for NLP model Bert.