Top 10 Open-Source Frameworks for AI and Machine Learning Models

Top 10 Open-Source Frameworks for AI and Machine Learning Models. List of best Machine Learning framework. Open source artificial intelligence frameworks.

Learn how to work Python and R

Learn how to use Python and R in conjunction with each other to utilize the best of both in a single data science project. An introduction for working with R within Python. An introductory guide to incorporate R in your workflow as a Python Data Scientist. In case, you’ll like to integrate Python in your workflow as an R Data Scientist

Learn Python from Zero - Full Fundamental Course for Beginners

Learn Python from Zero - Full Fundamental Course for Beginners: This course will provides you a full introduction into all of the core concepts in python like data types, reserved words etc. View this Python tutorial for beginners to learn Python programming from zero. Every topic explained in detail to make this best Python tutorial for beginners.

Dictionaries in Python - Learn how to work with Python Dictionaries

In this Python Dictionaries tutorial, you will learn how to work with Python Dictionaries, an incredibly helpful built-in data type that you will definitely use during your projects. In this Python dictionaries tutorial you'll cover the basic characteristics and learn how to access and manage dictionary data. Learn everything about Python dictionary; how they are created, accessing, adding and removing elements from them and, various built-in methods.

6 Free Python Programming Courses for Beginners in 2020

If you decide to learn Python online for FREE and looking for some awesome resources then you have come to the right place. Free Python courses online. Learn python programming from institutions like MIT, Microsoft and Georgia Tech: Introduction To Python Programming, Deep Learning Prerequisites: The Numpy Stack in Python, Python Core and Advanced, Master Python Complete Course, 2020 learning Python3.8 from beginner to the master, Programming with Python All in One

Python for Data Science and Machine Learning

This Python tutorial for Data Science and Machine Learning will kick-start your learning of Python concepts needed for data science, as well as programming in general. Understand how to use the Jupyter Notebook, Understanding of Python from the beginning, Learn to use Object Oriented Programming with classes, Learn how to use NumPy, Pandas, Seaborn, Matplotlib, Plotly, Scikit-Learn, Machine Learning, Tensorflow, and more!

Learn Python with Jupyter Notebook from Scratch

Python and Jupyter Notebooks for beginners: Learn Python with Jupyter Notebook from scratch. In this introductory beginners course we will learn about the basics of Python and Jupyter notebook. You'll learn: How to install Jupyter Notebook, How to run the Jupyter Notebook Server, Common Jupyter Commands, Python Expressions, Python Statements, Python Variables, Python Data Types, Python Operators, Python Loops, Python Functions, Jupyter Components, Notebook Dashboard, Explore Notebook Interface,....

Deep Learning in Go - Present and Future

Deep learning in Go? But why? And how? What’s next? Curious? Let’s explore it with a fun-filled, fast-paced deep dive into deep learning in Go. Learn how to build ‘deep learning’ models with Go to solve complex real-world challenges.

Building a Powerful Virtual Machine in JavaScript

This JavaScript tutorial explains how to build a powerful Virtual Machine in JavaScript. A flexible, extensible, register-based virtual machine. Support for signed, unsigned and floating point operations. A call stack. Interrupt capabilities. Ability to do memory mapping for IO. An assembly language with macro and module support. A higher level, C like language. We'll use and expand the library from the parser combinators from scratch series. And finally, to be able to take the whole thing into the browser and exend it to create a sort of fantasy console - an emulator for a machine that never existed

Introduction to Machine Learning

In this Machine Learning tutorial, you'll explore what machine learning is and how it works. You'll understand the differences between supervised learning and unsupervised learning. You'll even learn core concepts like regression models, classification models, clustering models, and dimension reduction models.

Top 10 Machine Learning Frameworks for Web Development

Top 10 Machine Learning Frameworks for Web Development. There are many machine learning framework used for the web development company. The web development with machine learning is going to change the IT world in the future as it is becoming popular day by day. These frameworks are written in different languages such as Python, Java, C++, Scala, etc.

ONNX-Go: Neural Networks made easy

ONNX-Go: Neural Networks made easy. Olivier introduces onnx-go, a package that gives the ability to read (and eventually to execute) machine learning models encoded in the Open Neural Network eXchange format in Go.

Artificial Intelligence (AI) Tutorial - Getting started with AI

Artificial Intelligence (AI) Tutorial - Getting started with Artificial Intelligence. In this Artificial Intelligence tutorial you will learn end to end about AI and it's vast domain. So this AI tutorial for beginners is an exhaustive tutorial for you to get started with AI.

Skorch: A scikit-learn compatible Neural Network library that wraps PyTorch

This talk is about the open source package skorch, a wrapper library that allows you to combine the best of sklearn and PyTorch. It covers when it makes sense to use skorch and highlights interesting features.

Top 10 Applications of Natural Language Processing (NLP)

Natural Language Processing (NLP): What it is and why it matters. What tasks can be solved with NLP? The scope is great and every day the number of tasks is increasing. In this post, you'll see top 10 Applications of Natural Language Processing. Natural Language Processing (NLP): Top 10 Applications to Know

Know what you don't know: Tools to understand uncertainty in DL

In this "Know what you don't know: Tools to understand uncertainty in Deep Learning", we want to bridge the gap between practical methods for Deep Learning and Bayesian Inference in a practical setting. We will start by introducing common problems in machine learning systems that arise from the lack of understanding of how uncertain models are when given specific inputs. This causes limitations on applications that need robust solutions and can impact people lives, such as healthcare, financial trading, and autonomous vehicles.

Machine Learning Crash Course

Machine Learning Crash Course - "This talk introduces machine learning through the lens of three use cases: Teaching a computer sign language (supervised learning), Predicting energy usage in Texas (time series data), Using machine learning to find your next job (content-based filtering). Each use case demonstrates techniques applicable in real-world machine learning problems."

Natural Language Processing

Natural Language Processing, or NLP for short, is comprehensively characterized as the programmed control of regular language, similar to discourse and content, by programming. The investigation of normal language handling has been around for...

Interpretable Machine Learning

Interpretable Machine Learning - Extracting human understandable insights from any Machine Learning model. A Guide for Making Black Box Models Explainable. Machine Learning doesn’t have to be a black box anymore. What use is a good model if we cannot explain the results to others. Interpretability is as important as creating a model.

Machine Learning Tutorial - Machine Learning Full Course For Beginners

This Machine Learning Tutorial - Machine Learning Full Course For Beginners covers what is Machine Learning, Machine Learning algorithms like linear regression, binary classification, decision tree, random forest and unsupervised algorithm like k means clustering in detail with complete hands on demo, Machine Learning interview questions to prepare you for the job interview.