Machine Learning In Just 5 Lines Of Code: Fast.ai New Release

Machine Learning In Just 5 Lines Of Code: Fast.ai New Release

Fast.ai makes it easy to migrate from PyTorch, Ignite, or any other PyTorch-based library, or use fastai in conjunction with other libraries. On Friday, Jeremy Howard’s fast.ai announced the release of super productive libraries along with a very handy machine learning book and also a course. Fast.ai is popular deep learning that provides high-level components to obtain state-of-the-art results in standard deep learning domains.

On Friday, Jeremy Howard’s fast.ai announced the release of super productive libraries along with a very handy machine learning book and also a course. Fast.ai is popular deep learning that provides high-level components to obtain state-of-the-art results in standard deep learning domains. Fast.ai allows practitioners to experiment, mix and match to discover new approaches. In short, to facilitate hassle-free deep learning solutions.

The libraries leverage the dynamism of the underlying Python language and the flexibility of the PyTorch library. 

Now the latest version, ‘fastai v2’ is a complete rewrite of fastai which is faster, easier, and more flexible, implementing new approaches to deep learning framework design.

Overview Of The New Releases

Fast.ai makes it very easy to migrate from plain PyTorch, Ignite, or any other PyTorch-based library, or even to use fastai in conjunction with other libraries. Users can use fastai’s GPU-accelerated computer vision library, along with your own training loop. They can also pick and choose with mixup and cutout augmentation, a uniquely flexible GAN training framework, which isn’t available in any other framework.


developers corner deep learning library fastai frameworks deep learning

Bootstrap 5 Complete Course with Examples

Bootstrap 5 Tutorial - Bootstrap 5 Crash Course for Beginners

Nest.JS Tutorial for Beginners

Hello Vue 3: A First Look at Vue 3 and the Composition API

Building a simple Applications with Vue 3

Deno Crash Course: Explore Deno and Create a full REST API with Deno

How to Build a Real-time Chat App with Deno and WebSockets

Convert HTML to Markdown Online

HTML entity encoder decoder Online

MXNet Tutorial: Complete Guide with Hands-On Implementation of Deep Learning Framework

The existing frameworks are programming language-specific. This problem is overcome by MXNet framework and it provides one system for different programming flavor. As the popularity and need for deep learning networks increase, there has been a lot of effort to build tools that ease the development of deep learning models. One such tool that we will discuss today is MXNet. You might be wondering what makes MXNet better than the already existing deep learning frameworks like Theano or Caffe.

Top 10 Deep Learning Sessions To Look Forward To At DVDC 2020

Looking to attend an AI event or two this year? Below ... Here are the top 22 machine learning conferences in 2020: ... Start Date: June 10th, 2020 ... Join more than 400 other data-heads in 2020 and propel your career forward. ... They feature 30+ data science sessions crafted to bring specialists in different ...

The Top 5 Deep Learning Libraries And Frameworks

Deep learning is a branch of machine learning, in essence, its the implementation of neural networks with more than a single hidden layer of neurons.

Hire Machine Learning Developers in India

We supply you with world class machine learning experts / ML Developers with years of domain experience who can add more value to your business.

Hire Machine Learning Developer | Hire ML Experts in India

We supply you with world class machine learning experts / ML Developers with years of domain experience who can add more value to your business.