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Welcome to the tools-repository wiki!

tools-repository

A repository of tools used for Data Science, Machine Learning, Deep Learning, Data Engineering, and DataOps revolving around reproducibility and compatability across operating systems

Tools

Repositories

• Github
• Bitbucket
• Gitlab
  • Why I choose Github? Popularity and 3rd party extensions

Python Environment & Package Managers

• Conda
• Pyenv
• venv
• virtualenv
• pip
• ?

CI/CD

• CircleCI
• TravisCI

Jupyter Hub

Docker Hub

Kubernetes

Ansible

Web Development

• Flask
• Django
• Tornado

Blog/CMS

• Pelican
• Wagtail

Spark

• PySpark
• Scala
• Performance Tuning

Unit Testing

• pytest
• unittest
• nose

Text Editors

• Sublime
• Atom
• Nano
• Vi/Vim/Emacs

IDEs

• PyCharm

AWS

• CloudFormation
• S3
• EC2
• RDS
• RedShift
• Aurora

GCP

• Cloud Storage
• Cloud SQL
• Compute Engine
• BigQuery
• Cloud Spanner

Airflow

• Redis
• Postgres
• Celery

Machine Learning Algorithms

• Linear Regression
• Logistic Regression
• Decision Trees
• K-Nearest Neighbors (KNN)
• K-Means
• Support Vector Machines (SVM)
• Principal Component Analysis (PCA)
• Gradient Boost
• Neural Networks
  • CNN
  • GNN

Might Put these in a separate repo README (and folder) or just leave this folder as the "link farm"

Artificial Intelligence Fundamentals:

• Algebraic concepts
• Linear Algebra
• Optimization Methods
• Numerical Algorithms
• Feature Selection
• Project Structure
  • Vectorization of Data
  • Feature Engineering
  • Handling missing data and outliers, imputation
  • Train/Validation/Test
  • Metrics

Deep Learning

Databases (non-cloud)

• ElasticSearch
• Postgres
• Redis
• TimeScaleDB
• MongoDB
• Cassandra
• Neo4J

Python

• OOP (practices)

  • Types of Classes: Static, Method, Data, etc
  • Decorators
  • 4 Pillars
  • etc

• FP (practices)

• Security

  • SSH
  • VPN
  • Ports
  • PHI/PII
  • HiTRUST
  • other?

Above would link to links in format below

Github

Lays out understanding, tutorial, etc Branching, Merging, Pull, Push, etc Multiple Accounts on same computer

Cheatsheet of commands: - command_1 - command_2 - command 3 Other helpful resources:

• subLink #1
• subLink #2
• subLink #3

Python Environment Management

• Link #1
• Link #2
• Link #3
• Cheatsheet of commands:
  • command_1
  • command_2
  • command 3

Python Package Management

• tool #1
• tool #2
• tool #3