Machine Learner

This list of resources is specifically targeted at Web Developers and Data Scientists…. so do with it what you will…This list borrows…


Everything You Need To Become A Machine Learner

This list of resources is specifically targeted at Web Developers and Data Scientists…. so do with it what you will…This list borrows heavily from multiple lists created by : sindresorhusarrow-up-right

Machine learning is a subfield of artificial intelligence, which is broadly defined as the capability of a machine to imitate intelligent human behavior. Artificial intelligence systems are used to perform complex tasks in a way that is similar to how humans solve problems.

The goal of AI is to create computer models that exhibit “intelligent behaviors” like humans, according to Boris Katzarrow-up-right, a principal research scientist and head of the InfoLab Group at CSAIL. This means machines that can recognize a visual scene, understand a text written in natural language, or perform an action in the physical world.

Machine learning is one way to use AI. It was defined in the 1950s by AI pioneer Arthur Samuelarrow-up-right as “the field of study that gives computers the ability to learn without explicitly being programmed.”

- \[📖\] Delivering Happinessarrow-up-right - \[📖\] Good to Great: Why Some Companies Make the Leap…And Others Don’tarrow-up-right - \[📖\] Hello, Startup: A Programmer’s Guide to Building Products, Technologies, and Teamsarrow-up-right - \[📖\] How Google Worksarrow-up-right - \[📖\] Learn to Earn: A Beginner’s Guide to the Basics of Investing and Businessarrow-up-right - \[📖\] Reworkarrow-up-right - \[📖\] The Airbnb Storyarrow-up-right - \[📖\] The Personal MBAarrow-up-right - \[ \] Facebook: Digital marketing: get startedarrow-up-right - \[ \] Facebook: Digital marketing: go furtherarrow-up-right - \[ \] Google Analytics for Beginnersarrow-up-right - \[ \] Moz: The Beginner’s Guide to SEOarrow-up-right - \[ \] Smartly: Marketing Fundamentalsarrow-up-right - \[ \] Treehouse: SEO Basicsarrow-up-right - \[🅤\]ꭏ App Monetizationarrow-up-right - \[🅤\]ꭏ App Marketingarrow-up-right - \[🅤\]ꭏ How to Build a Startuparrow-up-right


Natural language processing

Natural language processing is a field of machine learning in which machines learn to understand natural language as spoken and written by humans, instead of the data and numbers normally used to program computers. This allows machines to recognize language, understand it, and respond to it, as well as create new text and translate between languages. Natural language processing enables familiar technology like chatbots and digital assistants like Siri or Alexa.### Neural networksNeural networks are a commonly used, specific class of machine learning algorithms. Artificial neural networks are modeled on the human brain, in which thousands or millions of processing nodes are interconnected and organized into layers.

In an artificial neural network, cells, or nodes, are connected, with each cell processing inputs and producing an output that is sent to other neurons. Labeled data moves through the nodes, or cells, with each cell performing a different function. In a neural network trained to identify whether a picture contains a cat or not, the different nodes would assess the information and arrive at an output that indicates whether a picture features a cat.

Be familiar with how Machine Learning is applied at other companies


Be able to frame anMachine Learning problem

· [ ] AWS: Types of Machine Learning Solutionsarrow-up-right

· [📰] Apply Machine Learning to your Businessarrow-up-right

· [📰] Resilience and Vibrancy: The 2020 Data & AI Landscapearrow-up-right

· [📰] Software 2.0arrow-up-right

· [📰] Highlights from ICML 2020arrow-up-right

· [📰] A Peek at Trends in Machine Learningarrow-up-right

· [📰] How to deliver on Machine Learning projectsarrow-up-right

· [📰] Data Science as a Productarrow-up-right

· [📰] Customer service is full of machine learning problemsarrow-up-right

· [📰] Choosing Problems in Data Science and Machine Learningarrow-up-right

· [📰] Why finance is deploying natural language processingarrow-up-right

· [📰] The Last 5 Years In Deep Learningarrow-up-right

· [📰] Always start with a stupid model, no exceptions.arrow-up-right

· [📰] Most impactful AI trends of 2018: the rise ofMachine Learning Engineeringarrow-up-right

· [📰] Building machine learning products: a problem well-defined is a problem half-solved.arrow-up-right

· [📰] Simple considerations for simple people building fancy neural networksarrow-up-right

· [📰] Maximizing Business Impact with Machine Learningarrow-up-right

· [📖] AI Superpowers: China, Silicon Valley, and the New World Orderarrow-up-right

· [📖] A Human’s Guide to Machine Intelligencearrow-up-right

· [📖] The Future Computedarrow-up-right

· [📖] Machine Learning Yearning by Andrew Ngarrow-up-right

· [📖] Prediction Machines: The Simple Economics of Artificial Intelligencearrow-up-right

· [📖] Building Machine Learning Powered Applications: Going from Idea to Productarrow-up-right

· [ ] Coursera: AI For Everyonearrow-up-right

· [💻] Data Science for Everyonearrow-up-right

· [💻] Machine Learning with the Experts: School Budgetsarrow-up-right

· [💻] Machine Learning for Everyonearrow-up-right

· [💻] Data Science for Managersarrow-up-right

· [ ] Facebook: Field Guide to Machine Learningarrow-up-right

· [G] Introduction to Machine Learning Problem Framingarrow-up-right

· [ ] Pluralsight: How to Think About Machine Learning Algorithmsarrow-up-right

· [ ] State of AI Report 2020arrow-up-right

· [📺 ] Vincent Warmerdam: The profession of solving (the wrong problem) | PyData Amsterdam 2019arrow-up-right

· [📺 ] Hugging Face, Transformers | NLP Research and Open Source | Interview with Julien Chaumondarrow-up-right

· [📺 ] Vincent Warmerdam — Playing by the Rules-Based-Systems | PyData Eindhoven 2020arrow-up-right

· [📺 ] Building intuitions before building modelsarrow-up-right


Be familiar with data ethics

Be able to import data from multiple sources

Be able to setup data annotation efficiently

[📰] Create A Synthetic Image Dataset — The “What”, The “Why” and The “How”arrow-up-right


Be able to manipulate data with Numpy

Be able to manipulate data with Pandas

- **\[📰\]** Visualizing Pandas’ Pivoting and Reshaping Functionsarrow-up-right - **\[📰\]** A Gentle Visual Intro to Data Analysis in Python Using Pandasarrow-up-right - **\[📰\]** Comprehensive Guide to Grouping and Aggregating with Pandasarrow-up-right - **\[📰\]** 8 Python Pandas Value_counts() tricks that make your work more efficientarrow-up-right - **\[💻\]** pandas Foundationsarrow-up-right - **\[💻\]** Pandas Joins for Spreadsheet Usersarrow-up-right - **\[💻\]** Manipulating DataFrames with pandasarrow-up-right - **\[💻\]** Merging DataFrames with pandasarrow-up-right - **\[💻\]** Data Manipulation with pandasarrow-up-right - **\[💻\]** Optimizing Python Code with pandasarrow-up-right - **\[💻\]** Streamlined Data Ingestion with pandasarrow-up-right - **\[💻\]** Analyzing Marketing Campaigns with pandasarrow-up-right - **\[ \]** edX: Implementing Predictive Analytics with Spark in Azure HDInsightarrow-up-right - **\[📰\]** Modern Pandasarrow-up-right - **\[ \]** Modern Pandas (Part 1)arrow-up-right - **\[ \]** Modern Pandas (Part 2)arrow-up-right - **\[ \]** Modern Pandas (Part 3)arrow-up-right - **\[ \]** Modern Pandas (Part 4)arrow-up-right - **\[ \]** Modern Pandas (Part 5)arrow-up-right - **\[ \]** Modern Pandas (Part 6)arrow-up-right - **\[ \]** Modern Pandas (Part 7)arrow-up-right - **\[ \]** Modern Pandas (Part 8)arrow-up-right

Be able to manipulate data in spreadsheets

Be able to manipulate data in databases

Be able to use Linux

Resources:

Bash Proficiency In Under 15 Minutesarrow-up-right

Cheat sheet and in-depth explanations located below main article contents… The UNIX shell program interprets user…arrow-up-right

These Are The Bash Shell Commands That Stand Between Me And Insanityarrow-up-right

I will not profess to be a bash shell wizard… but I have managed to scour some pretty helpful little scripts from Stack…arrow-up-right

Bash Commands That Save Me Time and Frustrationarrow-up-right

Here’s a list of bash commands that stand between me and insanity.arrow-up-right

Life Saving Bash Scripts Part 2arrow-up-right

I am not saying they’re in any way special compared with other bash scripts… but when I consider that you can never…arrow-up-right

What Are Bash Aliases And Why Should You Be Using Them!arrow-up-right

A Bash alias is a method of supplementing or overriding Bash commands with new ones. Bash aliases make it easy for…arrow-up-right

BASH CHEAT SHEETarrow-up-right

My Bash Cheatsheet Index:arrow-up-right


holy grailarrow-up-right of learning bash

Be able to perform feature selection and engineering

Be able to experiment in a notebook

Be able to visualize data

Be able to model problems mathematically

Be able to setup project structure

Be able to version control code

Understanding Git (A Beginners Guide Containing Cheat Sheets & Resources) _Basic Git Work Flow._levelup.gitconnected.comarrow-up-right

Github Repositories That Will Teach You How To Code For Free! _Update: here’s a repo full of helpful repos:_levelup.gitconnected.comarrow-up-right

Be able to setup model validation


Be familiar with inner working of models

***Bays theorem is super interesting and applicable ==> — \[📰\]*** Naive Bayes classificationarrow-up-right


Be able to improve models


Be familiar with fundamental Machine Learning concepts

CNNarrow-up-right

[ ] edX: Data Science Essentialsarrow-up-right

[ 📺] Fast.ai: Deep Learning for Coder (2020)arrow-up-right

[ 📺] Lesson 0arrow-up-right

[📺 ] Lesson 1arrow-up-right

[📺 ] Lesson 2arrow-up-right

[📺 ] Lesson 3arrow-up-right

[📺 ] Lesson 4arrow-up-right

[ 📺] Lesson 5arrow-up-right

[ 📺] Lesson 6arrow-up-right

[ 📺] Lesson 7arrow-up-right

[📺 ] Lesson 8arrow-up-right

Implement models in scikit-learn


Be able to implement models in Tensorflow and Keras

Be able to implement models in PyTorch


Be able to implement models using cloud services

By Bryan Gunerarrow-up-right on August 30, 2021arrow-up-right.

Canonical linkarrow-up-right

Exported from Mediumarrow-up-right on August 31, 2021.

Last updated