Repository Index

Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier

• machine-learning
• deep-learning
• lstm
• human-activity-recognition

Debugging, monitoring and visualization for Python Machine Learning and Data Science

• ai
• deep-learning
• deeplearning
• machine-learning

[Legacy] Data & AI Notebook templates catalog organized by tools, following the IMO (input, model, output) framework for easy usage and discovery..

• templates
• opensource
• naas
• notebooks-templates

TranslatedCovers pre-training data, Tokenizer, Transformer, MoE,distributed training, Scaling Laws, inference & alignment .6 progressive code assignments for full-stack LLM learning

• gpu-programming
• llm
• nlp
• rl

A library for debugging/inspecting machine learning classifiers and explaining their predictions

• scikit-learn
• machine-learning
• xgboost
• lightgbm

Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.

• data-science
• python
• dag
• data-engineering

TensorFlow Tutorials

• tensorflow-tutorials
• convolutional-neural-networks
• recurrent-neural-networks

Algorithms for outlier, adversarial and drift detection

• anomaly
• outlier
• concept-drift
• detection

2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.

• machine-learning
• python
• statistics
• scikit-learn

Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.

• high-frequency-trading
• limit-order-book
• python
• machine-learning

An unsupervised learning framework for depth and ego-motion estimation from monocular videos

• deep-learning
• depth-prediction
• visual-odometry
• self-supervised-learning

Synthetic data generators for tabular and time-series data

• gan-architectures
• gan
• deep-learning
• synthetic-data

Complex code hides connections, workflows, and business risks.Unvibe complex code. Trace business workflows.

• business-logic
• code-analysis
• code-understanding
• codebase-analysis

ProtTrans is providing state of the art pretrained language models for proteins. ProtTrans was trained on thousands of GPUs from Summit and hundreds of Google TPUs using Transformers Models.

Instructional notebooks on music information retrieval.

• ipython-notebook
• music-information-retrieval
• python
• machine-learning

TorchXRayVision: A library of chest X-ray datasets and models. Classifiers, segmentation, and autoencoders.

• medical-imaging
• medical-ai
• deep-learning
• machine-learning

A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)

• drug-repurposing
• deep-learning
• drug-target-interactions
• toolkit

Neural question generation using transformers

• nlp
• nlg
• deep-learning
• transformer

Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier

• seq2seq
• tensorflow
• tensorflow-tutorials
• python

Utility functions for handling MIDI data in a nice/intuitive way.

"Neural Turing Machine" in Tensorflow

• tensorflow
• neural-turing-machines

Collection of tools and code examples to demonstrate best practices in using Amazon EC2 Spot Instances.

Foundation Models for Genomics & Transcriptomics

• genomics
• deep-learning
• transformer
• dna

FarmVibes.AI: Multi-Modal GeoSpatial ML Models for Agriculture and Sustainability

• agriculture
• ai
• geospatial
• geospatial-analytics