Data Science Resources

courses I have taken

• Udacity

  • AWS Machine Learning Engineer
  • AI for Healthcare
  • AWS Machine Learning Foundations
  • Natural Language Processing with Attention Models
  • chatGPT Prompt Engineering for Developers

Story Telling (Data Visualization) Books

• Resonate
• Storytelling with Data
• Visualize This

Data Visualization

• Awesome Panel
• hvplot user guide
• Beautiful Python Visualization Dashboard With Panel/Hvplot: Thu Vu
• Panel
• Data science

ML Interpretability:

• ML Interpretability: SHAP/LIME

• ML Interpletability book

• InterpletML

• Explainable Machine Learning for Scientific insights and Discoveries

• An introduction to explainable AI with Shapley Values

• Amazon SageMaker clarify

• Why should I Trust You

Model Versioning

Version control in data science can be tricky, because there are many pieces involved that can be hard to track, such as large amounts of data, model versions, seeds, and hyperparameters. The following resources offer useful methods and tools for managing model versions and large amounts of data

• How to Version Control Your Production Machine Learning Models
• Version Control ML Model

Machine Learning University with Visual explanation

• Machine Learning University

Machine Learning Algorithms

• Linear Regression
  • Linear Regression

Data Versioning tools

• dvc

ML Debugging

• ML Debugging Andrej karpathy
• How to trust Your Deep Learning Code

hyperparameters tuning

• hyperparameters tuning

Model Calibration

• Lee Richardson and Taylor Pospisil
• Pleiss

Top 6 Errors Novice Machine Learning Engineers Make

• Christopher Dossman

Machine Learning Systems Design

Deployment - Prediction Service

Log and wait

Faire

Machine learning books

• Machine Learning from the scratch Derivations in concept and Code
• Deep Learning Fundamentals with Sebastian Raschka

Automated Canary Analysis with Kayenta

• Automated Canary Analysis

Privacy

• Privacy-preserving AI for Synthetic and Anonymous Health Data

Kubernates

• An introduction to Kubernates by Jeremy Jordan
• Inspector gadget is a tool designed to introspect and debug Kubernetes applications using eBPF
• Learnk8s

Feature Store

• Feature Store: A special kind of database (such as SageMaker Feature Store) that can store machine learning inputs. It is often characterized by support for batch (training) workloads, low-latency (real-time inference) workloads, and search.
• Feature Group: A logical grouping of features that can be discovered together. You might group features by topic or category, such as “weather” or “top secret”.

• Feature Stores: A Hierarchy of Needs
• Developing Scalable Feature Engineering DAGs
• Eugen Yan
• Amazon Sagemaker

Transfer Learning

• CS231n Convolutional Neural Networks for Visual Recognition
• Final Project Reports and Posters

Gradient Descent optimization optimization algorithms

• An overview of gradient descent optimization algorithms

Fine tuning models

• FINETUNING TORCHVISION MODELS
• Transfer learning and fine-tuning

Prebuilt Docker Images

• Prebuilt Docker Images
• Prebuilt Amazon SageMaker Docker Images for Scikit-learn and Spark ML
• Using Docker containers with SageMaker
• Building your own TensorFlow container
• Extending our PyTorch containers
• Example Notebooks: Use Your Own Algorithm or Model
• Advanced Functionality in SageMaker

Useful Pandas

• Useful Pandas

Useful Stack Overflow

Rebound is a command-line tool that instantly fetches Stack Overflow results when an exception is thrown. Just use the rebound command to execute your file.

• Rebound

Useful Sagemaker

• Instance auto shutdown
• Save Costs
• Develop, Train, Optimize and Deploy Scikit-Learn Random Forest
• AWS EVENTS
• certification resources

Useful Bayesian

• Aki Vehtari

Distributed Databases

• What is distributed databases
• Distributed Data Processing

Useful Autogluon

• Autogluon

EHR FHIR

• EDA
• Synthea Dataset
• FHIR starter: Parse healthcare bundles into tables

Useful Stack Overflow

• Stack Command line

The Practical Guides for Large Language Models

• [https://github.com/masinde70/LLMsPracticalGuide]