mlxtend

A library consisting of useful tools for data science and machine learning tasks.

Neural Networks and Deep Learning

Code samples for my book "Neural Networks and Deep Learning" [DEEP LEARNING].

ScikitLearn

Julia implementation of the scikit-learn API.

neon

Nervana's [high-performance](https://github.com/soumith/convnet-benchmarks) Python-based Deep Learning framework [DEEP LEARNING]. **[Deprecated]**

stacked_generalization

Implementation of machine learning stacking technique as a handy library in Python.

Cogitare

A Modern, Fast, and Modular Deep Learning and Machine Learning framework for Python.

Optunity examples

Examples demonstrating how to use Optunity in synergy with machine learning libraries.

Training Site Reliability Engineers: What Your Organization Needs to Create a Learning Program

Training Site Reliability Engineers: What Your Organization Needs to Create a Learning Program - Education

a very short history of #datascience

_The story of how data scientists became sexy is mostly the story of the coupling of the mature discipline of statistics with a very young one--computer science. The term “Data Science” has emerged only recently to specifically designate a new profession that is expected to make sense of the vast stores of big data. But making sense of data has a long history and has been discussed by scientists, statisticians, librarians, computer scientists and others for years. The following timeline traces the evolution of the term “Data Science” and its use, attempts to define it, and related terms._

Vuejs 2 Authentication Tutorial

on Auth0 blog

DevOpsLinks

A weekly newsletter about SRE, SysAdmin and DevOps news, tools, tutorials and opinions.

Introduction to machine learning with scikit-learn

IPython notebooks from Data School's video tutorials on scikit-learn.

What is Data Science @ O'reilly

_Data scientists combine entrepreneurship with patience, the willingness to build data products incrementally, the ability to explore, and the ability to iterate over a solution. They are inherently interdisciplinary. They can tackle all aspects of a problem, from initial data collection and data conditioning to drawing conclusions. They can think outside the box to come up with new ways to view the problem, or to work with very broadly defined problems: “here’s a lot of data, what can you make from it?”_

The sexiest job of 21st century

_Data scientists today are akin to Wall Street “quants” of the 1980s and 1990s. In those days people with backgrounds in physics and math streamed to investment banks and hedge funds, where they could devise entirely new algorithms and data strategies. Then a variety of universities developed master’s programs in financial engineering, which churned out a second generation of talent that was more accessible to mainstream firms. The pattern was repeated later in the 1990s with search engineers, whose rarefied skills soon came to be taught in computer science programs._

TDB

TensorDebugger (TDB) is a visual debugger for deep learning. It features interactive, node-by-node debugging and visualization for TensorFlow.

Introduction to Machine Learning with Python

Notebooks and code for the book "Introduction to Machine Learning with Python"

TutorGPT

Dynamic few-shot metaprompting for the task of tutoring. 

Deep Diamond

A fast Clojure Tensor & Deep Learning library

fastmath

A collection of functions for mathematical and statistical computing, macine learning, etc., wrapping several JVM libraries

golearn

Machine learning for Go.

Software Development Resources for Data Scientists

_Data scientists concentrate on making sense of data through exploratory analysis, statistics, and models. Software developers apply a separate set of knowledge with different tools. Although their focus may seem unrelated, data science teams can benefit from adopting software development best practices. Version control, automated testing, and other dev skills help create reproducible, production-ready code and tools._

go-ml-transpiler

An open source Go transpiler for machine learning models.

therfoo

An embedded deep learning library for Go.

dataframe-go

Dataframes for machine-learning and statistics (similar to pandas).

Bitfalls

Technical news, solidity tutorials, and skeptical research. EN and HR languages.

goml

Machine learning library written in pure Go.

Create Coding Tutorials

Takes your code and develops a self-paced tutorial for your students.

hopfield-networks

Hopfield Networks for unsupervised learning in Haskell. **[Deprecated]**

PySpark Cheatsheet

PySpark Cheatsheet - Tutorials

Bitcoin and Cryptocurrency Course

Bitcoin and Cryptocurrency Technologies course. 12 videos, each 45-90 mins.

gold

A reinforcement learning library.

Smile

Statistical Machine Intelligence & Learning Engine.

tensor-js

A deep learning library for the browser, accelerated by WebGL and WebAssembly.

Knet

Koç University Deep Learning Framework.

Referral Marketing

and [Mobile Referral Marketing](https://www.referralsaasquatch.com/ultimate-guide-to-mobile-referral-marketing/) can give you word-of-mouth growth. For inspiration check [51 Best Referral Program Examples of 2016](https://www.referralsaasquatch.com/ultimate-guide-to-mobile-referral-marketing/). Thes

Data science your way

Data science your way - Tutorials

DataCamp Cheatsheets

Cheatsheets for data science.

Weka

Weka is a collection of machine learning algorithms for data mining tasks.

SystemML

flexible, scalable machine learning (ML) language.

Tribou

A machine learning library written in Java by Oracle.

kNear

JavaScript implementation of the k nearest neighbors algorithm for supervised learning.

MLJ

A Julia machine learning framework.

8 Email Pitch Templates to Partner with Influencers

by Sapph. Nice guides & examples for asking promotion, contribution, partnership or review from the influencer. Customize and use them!

Homemade Machine Learning

Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

Vue.js Feed

The latest Vue.js news, tutorials, plugins, and more. Made with Vue.js and Laravel.

Hugging Face Diffusion Models Course

Python materials for the online course on diffusion models by [@huggingface](https://github.com/huggingface).

Clare Corthell

The Open Source Data Science Masters

Colossyan

Learning & Development focused video creator. Use AI avatars to create educational videos in multiple languages.