- Book: Atomic Habits
- Book: A Human's Guide to Machine Intelligence
- Book: Deep Work
- Book: Emotional Intelligence
- Book: Good to Great: Why Some Companies Make the Leap...And Others Don't
- Book: How to Win Friends & Influence People
- Book: How Google Works
- Book: Influence: The Psychology of Persuasion
- Book: Leaders Eat Last: Why Some Teams Pull Together and Others Don't
- Book: Learn to Earn: A Beginner's Guide to the Basics of Investing and Business
- Book: Multipliers: How the Best Leaders Make Everyone Smarter
- Book: Outliers: The Story of Success
- Book: Rich Dad Poor Dad
- Book: Rework
- Book: Soft Skills: The software developer's life manual
- Book: The Power of Broke
- Book: The 10X Rule: The Only Difference Between Success and Failure
- Book: The Airbnb Story
- Book: The Millionaire Fastlane
- Book: The New One Minute Manager
- Book: The Subtle Art of Not Giving a F**k
- Book: Delivering Happiness: A Path to Profits, Passion, and Purpose
- Pluralsight: Productivity for Programmers
- Facebook: Digital marketing: get started
- Facebook: Digital marketing: go further
- Google Analytics for Beginners
- Google: Fundamentals of Digital Marketing
- Hello, Startup: A Programmer's Guide to Building Products, Technologies, and Teams
- Smartly: Marketing Fundamentals
- Treehouse: SEO Basics
- The Personal MBA: Master the Art of Business
- Thoughtbot: Analytics for Developers
- Udacity: App Monetization
- Udacity: App Marketing
- Udacity: Get Your Startup Started
- Udacity: How to Build a Startup
- AWS: Types of Machine Learning Solutions
- Book: AI Superpowers: China, Silicon Valley, and the New World Order
- Book: The Future Computed
- Book: Machine Learning Yearning by Andrew Ng
- Book: Prediction Machines: The Simple Economics of Artificial Intelligence
- Coursera: AI For Everyone
- Datacamp: Case Studies in Statistical Thinking
- Datacamp: Customer Segmentation in Python
- Datacamp: HR Analytics in Python: Predicting Employee Churn
- Datacamp: Machine Learning with the Experts: School Budgets
- Datacamp: Analyzing Police Activity with pandas
- Datacamp: Data Science for Managers
- Facebook: Field Guide to Machine Learning
- Google: Art and Science of Machine Learning
- Google: How Google does Machine Learning
- Google: Introduction to Machine Learning Problem Framing
- Microsoft: Define an AI strategy to create business value
- Microsoft: Discover ways to foster an AI-ready culture in your business
- Microsoft: Identify guiding principles for responsible AI in your business
- Microsoft: Introduction to AI technology for business leaders
- Pluralsight: How to Think About Machine Learning Algorithms
- Udacity: Problem Solving with Advanced Analytics
- Datacamp: Intro to Python for Data Science
- Pluralsight: Working with Multidimensional Data Using NumPy
- Datacamp: pandas Foundations
- Datacamp: Manipulating DataFrames with pandas
- Datacamp: Merging DataFrames with pandas
- Datacamp: Optimizing Python Code with pandas
- Datacamp: Streamlined Data Ingestion with pandas
- Pandas Exercises
- Datacamp: Spreadsheet basics
- Datacamp: Data Analysis with Spreadsheets
- Datacamp: Intermediate Spreadsheets for Data Science
- Datacamp: Pivot Tables with Spreadsheets
- edX: Analyzing and Visualizing Data with Excel
- Book: Learn SQL the hard way
- Codecademy: SQL Track
- Codecademy: SQL: Table Transformation
- Codecademy: SQL: Analyzing Business Metrics
- Datacamp: Intro to SQL for Data Science
- Datacamp: Joining Data in PostgreSQL
- Datacamp: Querying with TransactSQL
- Datacamp: Introduction to Databases in Python
- Khan Academy: SQL
- Launch School: Introduction to SQL
- Treehouse: Using Databases in Python
- Udacity: SQL for Data Analysis
- Udacity: Intro to relational database
- Udacity: Database Systems Concepts & Design
- Bash Academy
- Bash Programming
- Codecademy: Learn the Command Line
- CONQUERING THE COMMAND LINE
- Datacamp: Introduction to Shell for Data Science
- LaunchSchool: Introduction to Commandline
- Learn Enough Command Line to be dangerous
- Thoughtbot: Mastering the Shell
- Thoughtbot: tmux
- Udacity: Linux Command Line Basics
- Udacity: Linux Web Servers
- Udacity: Shell Workshop
- Udacity: Web Tooling & Automation
- Web Bos: Command Line Power User
- Datacamp: Analyzing Social Media Data in Python
- Datacamp: Dimensionality Reduction in Python
- Datacamp: Preprocessing for Machine Learning in Python
- Datacamp: Data Types for Data Science
- Datacamp: Cleaning Data in Python
- Datacamp: Importing Data in Python (Part 2)
- Datacamp: Importing & Managing Financial Data in Python
- Datacamp: Manipulating Time Series Data in Python
- edX: Data Science Essentials
- Google: Feature Engineering
- Udacity: Creating an Analytical Dataset
- Datacamp: Introduction to Data Visualization with Python
- Datacamp: Introduction to Seaborn
- Datacamp: Data Visualization with Seaborn
- Datacamp: Visualizing Time Series Data in Python
- Datacamp: Visualizing Geospatial Data in Python
- Datacamp: Interactive Data Visualization with Bokeh
- Udacity: Data Visualization in Tableau
- Paper: A Neural Probabilistic Language Model
- Paper: Efficient Estimation of Word Representations in Vector Space
- Paper: Sequence to Sequence Learning with Neural Networks
- Paper: Neural Machine Translation by Jointly Learning to Align and Translate
- Paper: Attention Is All You Need
- Paper: BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
- Paper: XLNet: Generalized Autoregressive Pretraining for Language Understanding
- Paper: Synonyms Based Term Weighting Scheme: An Extension to TF.IDF
- Paper: RoBERTa: A Robustly Optimized BERT Pretraining Approach
- Paper: GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
- Paper: Amazon.com Recommendations Item-to-Item Collaborative Filtering
- Paper: Collaborative Filtering for Implicit Feedback Datasets
- Paper: BPR: Bayesian Personalized Ranking from Implicit Feedback
- Paper: Factorization Machines
- Paper: Wide & Deep Learning for Recommender Systems
- Paper: Neural Factorization Machines for Sparse Predictive Analytics
- Whitepaper: Architecting for the Cloud AWS Best Practices
- Whitepaper: AWS Well-Architected Framework
- Whitepaper: AWS Security Best Practices
- Whitepaper: Blue/Green Deployments on AWS
- Whitepaper: Microservices on AWS
- Whitepaper: Optimizing Enterprise Economics with Serverless Architectures
- Whitepaper: Practicing Continuous Integration and Continuous Delivery on AWS
- Whitepaper: Running Containerized Microservices on AWS
- Whitepaper: Serverless Architectures with AWS Lambda
- Book: Basics of Linear Algebra for Machine Learning
- Book: Doing Math with Python
- Datacamp: Statistical Thinking in Python (Part 1)
- Datacamp: Statistical Thinking in Python (Part 2)
- edX: Essential Statistics for Data Analysis using Excel
- Essence of Linear Algebra
- Khan Academy: Precalculus
- Khan Academy: Probability
- Khan Academy: Differential Calculus
- Khan Academy: Multivariable Calculus
- Khan Academy: Linear Algebra
- MIT: 18.06 Linear Algebra (Professor Strang): Lec 1-5
- The Math of Intelligence
- Udacity: Algebra Review
- Udacity: Differential Equations in Action
- Udacity: Eigenvectors and Eigenvalues
- Udacity: Linear Algebra Refresher
- Udacity: Statistics
- Udacity: Intro to Descriptive Statistics
- Udacity: Intro to Inferential Statistics
- AWS: Semantic Segmentation Explained
- AWS: The Elements of Data Science
- AWS: Understanding Neural Networks
- Book: Pattern Recognition and Machine Learning
- Book: Deep Learning Illustrated: A Visual, Interactive Guide to Artificial Intelligence
- Coursera: Neural Networks and Deep Learning
- Datacamp: Clustering Methods
- Datacamp: Network Analysis in Python (Part 1)
- Datacamp: Network Analysis in Python (Part 2)
- Datacamp: Extreme Gradient Boosting with XGBoost
- Datacamp: Introduction to PySpark
- Datacamp: Building Recommendation Engines with PySpark
- Datacamp: Statistical Simulation in Python
- Datacamp: Foundations of Predictive Analytics in Python (Part 1)
- Elements of AI
- edX: Principles of Machine Learning
- edX: Data Science Essentials
- edX: Principles of Machine Learning
- edX: Implementing Predictive Analytics with Spark in Azure HDInsight
- Google: Launching into Machine Learning
- Google: Clustering
- Google: Recommendation Systems
- Grokking Deep Learning
- How Deep Neural Networks work
- How CNN works
- Jason Machine Learning 101 Slides
- Make Your Own Neural Network
- MIT: 6.S191: Introduction to Deep Learning
- Pluralsight: Understanding Algorithms for Recommendation Systems
- Pluralsight: Deep Learning: The Big Picture
- Udacity: A Friendly Introduction to Machine Learning
- Udacity: Intro to Data Analysis
- Udacity: Intro to Data Science
- Udacity: Intro to Machine Learning
- Udacity: Reinforcement Learning
- Udacity: Deep Learning
- Udacity: Intro to Artificial Intelligence
- Udacity: Classification Models
- Udacity: Segmentation and Clustering
- Coursera: Structuring Machine Learning Projects
- Datacamp: Conda Essentials
- Datacamp: Creating Robust Python Workflows
- Datacamp: Software Engineering for Data Scientists in Python
- Datacamp: Designing Machine Learning Workflows in Python
- Datacamp: Object-Oriented Programming in Python
- Full Stack Deep Learning
- Treehouse: Object Oriented Python
- Treehouse: Setup Local Python Environment
- Udacity: Writing READMEs
- Book: Deep Learning for Computer Vision with Python
- Book: Practical Python and OpenCV
- Coursera: Convolutional Neural Networks
- Datacamp: Biomedical Image Analysis in Python
- Google: ML Practicum: Image Classification
- Udacity: Introduction to Computer Vision
- A friendly introduction to Recurrent Neural Networks
- Coursera: Sequence Models
- Coursera: Natural Language Processing in TensorFlow
- Datacamp: Advanced NLP with spaCy
- Datacamp: Building Chatbots in Python
- Datacamp: Feature Engineering for NLP in Python
- Datacamp: Natural Language Processing Fundamentals in Python
- Datacamp: Regular Expressions in Python
- Datacamp: Sentiment Analysis in Python
- fast.ai Code-First Intro to Natural Language Processing
- RNN and LSTM
- Spacy Tutorial
- TextBlob Tutorial Series
- Treehouse: Regular expression
- Datacamp: Machine Learning for Finance in Python
- Datacamp: Introduction to Time Series Analysis in Python
- Datacamp: Machine Learning for Time Series Data in Python
- Datacamp: Intro to Portfolio Risk Management in Python
- Datacamp: Financial Forecasting in Python
- Datacamp: Intro to Financial Concepts using Python
- Kaggle: Time Series with Siraj
- Udacity: Machine Learning for Trading
- Udacity: Time Series Forecasting
- Datacamp: Supervised Learning with scikit-learn
- Datacamp: Unsupervised Learning in Python
- Datacamp: Machine Learning with Tree-Based Models in Python
- Datacamp: Introduction to Linear Modeling in Python
- Datacamp: Linear Classifiers in Python
- Pluralsight: Building Machine Learning Models in Python with scikit-learn
- Coursera: Introduction to Tensorflow
- Coursera: Convolutional Neural Networks in TensorFlow
- Deeplizard: Keras - Python Deep Learning Neural Network API
- Deep Learning with Python
- Datacamp: Deep Learning in Python
- Datacamp: Convolutional Neural Networks for Image Processing
- Datacamp: Introduction to TensorFlow in Python
- Google: Keras Blog
- Google: Intro to Tensorflow
- Google: Machine Learning Crash Course
- Pluralsight: Deep Learning with Keras
- Udacity: Intro to TensorFlow for Deep Learning
- Deeplizard: Neural Network Programming - Deep Learning with PyTorch
- Udacity: Intro to Deep Learning with PyTorch
- AWS: Amazon Transcribe Deep Dive: Using Feedback Loops to Improve Confidence Level of Transcription
- AWS: Build a Text Classification Model with AWS Glue and Amazon SageMaker
- AWS: Deep Dive on Amazon Rekognition: Building Computer Visions Based Smart Applications
- AWS: Hands-on Rekognition: Automated Video Editing
- AWS: Introduction to Amazon Comprehend
- AWS: Introduction to Amazon Comprehend Medical
- AWS: Introduction to Amazon Elastic Inference
- AWS: Introduction to Amazon Forecast
- AWS: Introduction to Amazon Lex
- AWS: Introduction to Amazon Personalize
- AWS: Introduction to Amazon Polly
- AWS: Introduction to Amazon SageMaker Ground Truth
- AWS: Introduction to Amazon SageMaker Neo
- AWS: Introduction to Amazon Transcribe
- AWS: Introduction to Amazon Translate
- AWS: Introduction to AWS Marketplace - Machine Learning Category
- AWS: Machine Learning Exam Basics
- AWS: Neural Machine Translation with Sockeye
- AWS: Process Model: CRISP-DM on the AWS Stack
- AWS: Satellite Image Classification in SageMaker
- edX: Amazon SageMaker: Simplifying Machine Learning Application Development
- Coursera: Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
- Datacamp: Model Validation in Python
- Datacamp: Parallel Computing with Dask
- Google: Testing and Debugging
- Acloudguru: AWS Certified Machine Learning - Specialty
- Acloudguru: AWS Certified Developer - Associate
- Acloudguru: AWS Certification Preparation Guide
- AWS: Exam Readiness: AWS Certified Developer – Associate
- AWS: Thirty Serverless Architectures in 30 Minutes
- Pluralsight: AWS Developer: The Big Picture
- Pluralsight: AWS Networking Deep Dive: Virtual Private Cloud (VPC)
- Pluralsight: AWS VPC Operations
- Pluralsight: Building Applications Using Elastic Beanstalk
- Udemy: AWS Concepts
- Udemy: Serverless Concepts
- Udemy: AWS Certified Developer - Associate 2018
- Codecademy: Deploy a Website
- Pluralsight: Hands-on Ansible
- Pluralsight: Docker and Containers: The Big Picture
- Pluralsight: Docker and Kubernetes: The Big Picture
- Servers for Hackers Series
- The Hacker's Guide to Scaling Python
- Udacity: HTTP & Web Servers
- Udacity: Intro to DevOps
- Udacity: Deploying Applications with Heroku
- Udacity: Developing Scalable Apps in Python
- Udacity: Configuring Linux Web Servers
- Udacity: Scalable Microservices with Kubernetes
- Udacity: Intro to Hadoop and MapReduce
- Datacamp: Customer Analytics & A/B Testing in Python
- Udacity: A/B Testing
- Udacity: A/B Testing for Business Analysts
- Pluralsight: Test-driven Development: The Big Picture
- Test Driven Development with Python
- Thoughtbot: Fundamentals of TDD
- Treehouse: Python Testing
- Udacity: Software Analysis & Testing
- Udacity: Software Testing
- Udacity: Software Debugging
- Book: A Byte of Python
- Book: Automate the boring stuff with python
- Book: Dive into Python 3
- Book: Learn Python The Hard way
- Book: Python 201
- Book: Python Anti-Patterns
- Book: Real Python
- Book: The Python 3 Standard Library By Example
- Codecademy: Learn Python
- Cognitiveclass.ai: Python for Data Science
- Datacamp: Python for R Users
- Datacamp: Importing Data in Python (Part 1)
- Datacamp: Intermediate Python for Data Science
- Datacamp: Python Data Science Toolbox (Part 1)
- Datacamp: Python Data Science Toolbox (Part 2)
- Datacamp: Intro to Python for Finance
- Datacamp: Writing Efficient Python Code
- Datacamp: Writing Functions in Python
- edX: Introduction to Python for Data Science
- edX: Programming with Python for Data Science
- Google's Python Class
- Treehouse: Python Basics
- Treehouse: Python collections
- Treehouse: Date and Time
- Treehouse: CSV And JSON
- Treehouse: Functional Programming with Python
- Treehouse: Python Decorators
- Treehouse: Write Better Python
- Thoughtbot: Regular Expressions
- TheNewBoston: Python Programming Tutorials
- Udacity: Introduction to Python Programming
- Udacity: Programming Foundations with Python
- Udacity: What is Programming?
- Writing Idiomatic Python 3
- Codecademy: Learn Git
- Codeschool: Try Git
- Code School: Git Real
- Datacamp: Introduction to Git for Data Science
- Git-Game
- Git Immersion
- Launch School: Intro to Git and GitHub
- Learn enough git to be dangerous
- Thoughtbot: Mastering Git
- Treehouse: Git Basics
- Udacity: GitHub & Collaboration
- Udacity: How to Use Git and GitHub
- Udacity: Version Control with Git
- Book: Hello Web App
- Book: Two scoops of Django
- Book: Refactoring UI
- Codecademy: HTML Projects
- Codecademy: Learn HTML
- Codecademy: CSS Grid
- Codecademy: Introduction to Javascript
- Codecademy: Learn CSS
- Codecademy: Learn Color Design
- Codecademy: Learn SASS
- Codecademy: Learn responsive design
- Codecademy: Make a website
- Codecademy: Learn ReactJS: Part I
- Codecademy: Learn ReactJS: Part II
- Codecademy: Learn JavaScript
- Codecademy: Jquery Iterators
- Codecademy: Jquery Track
- Codecademy: Learn Ruby
- Code School: Fundamentals of Design
- Code School: Blasting Off with Bootstrap
- Django Best Practices
- Django Girls Tutorial
- Eloquent Javascript
- (ES6) - Beau teaches JavaScript
- ES6
- Javascript for Cats
- JS for Beginners
- JS DOM
- Learn Python Django Web
- Launch School: Introduction to HTTP
- Learning JavaScript Design Patterns
- PyLadies Django Workshop
- Pluralsight: UX Fundamentals
- Pluralsight: HTML, CSS, and JavaScript: The Big Picture
- Pluralsight: CSS Positioning
- Pluralsight: Introduction to CSS
- Pluralsight: CSS: Specificity, the Box Model, and Best Practices
- Pluralsight: CSS: Using Flexbox for Layout
- Pluralsight: Using The Chrome Developer Tools
- Thoughtbot: Design for Developers
- Thoughtbot: Bourbon Smash
- Treehouse: Django Basics
- Treehouse: Customizing Django Templates
- Treehouse: HTML
- Treehouse: HTML Forms
- Treehouse: HTML Tables
- Treehouse: HTML Video and Audio
- Treehouse: How to make a website
- Treehouse: Responsive Layout
- Treehouse: Accessibility
- Treehouse: Website Optimization
- Treehouse: Frontend Optimization
- Treehouse: Gulp Basics
- Treehouse: CSS Best Practices
- Treehouse: CSS Beyond the Basics
- Treehouse: CSS Layout Basics
- Treehouse: CSS Selectors
- Treehouse: Modular CSS with Sass
- Treehouse: SASS Basics
- Treehouse: AJAX Basics
- Treehouse: Interactive webpages with JS
- Treehouse: Javascript Loops, Arrays and Objects
- Treehouse: Javascript Basics
- Treehouse: jQuery Basics
- Treehouse: Javascript Booleans
- Treehouse: Javascript Foundations
- Treehouse: Console Foundations
- Treehouse: Object-Oriented JavaScript
- Udacity: Authentication & Authorization: OAuth
- Udacity: Intro to Backend
- Udacity: Designing RESTful APIs
- Udacity: Client-Server Communication
- Udacity: HTML and CSS Syntax
- Udacity: Intro to HTML and CSS
- Udacity: HTML5 Canvas
- Udacity: Build high conversion web forms
- Udacity: Front End Frameworks
- Udacity: Responsive Web Design Fundamentals
- Udacity: Responsive Images
- Udacity: Build a blog
- Udacity: Offline Web Applications
- Udacity: Website Performance Optimization
- Udacity: Web Accessibility
- Udacity: Browser Rendering Optimization
- Udacity: Intro to Progressive Web Apps
- Udacity: Asynchronous JavaScript Requests
- Udacity: ES6 - JavaScript Improved
- Udacity: Intro to Javascript
- Udacity: Intro to AJAX
- Udacity: Intro to Jquery
- Udacity: Javascript Design Patterns
- Udacity: JavaScript Promises
- Udacity: Object Oriented JS 1
- Udacity: Object Oriented JS 2
- Udacity: JavaScript and the DOM
- Udemy: Understanding Typescript
- Wes Bos: Javascript 30
- Codecademy: Big O
- Crashcourse: Computer Science
- Grokking Algorithms
- Khan Academy: Data Structures
- Tech Interview Handbook
- Udacity: Computer Networking
- Udacity: Compilers: Theory and Practice
- Udacity: Intro to Algorithms
- Udacity: Intro to Computer Science
- Udacity: Intro to Operating Systems
- Udacity: Intro to Theoretical Computer Science
- Udacity: Programming Languages
- Udacity: Networking for Web Developers
- Launch School: Agile Planning
- Pluralsight: Product Owner Fundamentals
- Pluralsight: Scrum Master Fundamentals - Foundations
- Pluralsight: Security Awareness: Basic Concepts and Terminology
- Pluralsight: Secure Software Development
- Pluralsight: Clean Architecture: Patterns, Practices, and Principles
- Thoughtbot: Software Development Process
- Thoughtbot: Refactoring
- Udacity: Design of Computer Programs
- Udacity: Product Design
- Udacity: Rapid Prototyping
- Udacity: Software Architecture and Design
- Udacity: Software Development Process
- Udacity: Full Stack Foundations