Machine Learning and Computer Vision Engineer - Technical Interview Questions

Generation of diagrams like flowcharts or sequence diagrams from text in a similar manner as markdown

Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.

A light-weight, flexible, and expressive statistical data testing library

A playbook for systematically maximizing the performance of deep learning models.

Visualizations for machine learning datasets

PyMC educational resources

Statistical Rethinking Course for Jan-Mar 2023

Examples and guides for using the OpenAI API

High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI …

Best Practices on Recommendation Systems

Samples for use with MLOps

Merlin Systems provides tools for combining recommendation models with other elements of production recommender systems (like feature stores, nearest neighbor search, and exploration strategies) in…

A topic-centric list of HQ open datasets.

Python package built to ease deep learning on graph, on top of existing DL frameworks.

A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)

12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphic…

Factorization Machine for regression and classification

Public repo for DeepLearning.AI MLEP Specialization

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

Deep recommender models using PyTorch.

ML powered analytics engine for outlier detection and root cause analysis.

A curated list of references for MLOps

A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX

An adversarial example library for constructing attacks, building defenses, and benchmarking both

Source code/webpage/demos for the What-If Tool

Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.