A visual introduction to probability and statistics.

In this article, learn how to deploy a machine learning model in production using Flask framework in Python.

In this post, I'll discuss how to use convolutional neural networks for the task of semantic image segmentation. Image segmentation is a computer vision task in which we label specific regions of an image according to what's being shown.

Are you a tier 2 or tier 3 college student looking to get a high paying job or internship? We are here to help you provide with related roadmaps.

Looking for papers with code? If so, this GitHub repository, a clearinghouse for research papers and their corresponding implementation code, is definitely worth checking out.

List of 25 best machine learning and data science github repositories from 2018 with projects divided into different categories.

DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers. - mozilla/DeepSpeech

Tutorials, assignments, and competitions for MIT Deep Learning related courses. - lexfridman/mit-deep-learning

Cloud Native Presentation Slides with Jupyter Notebook + Reveal.js - GitHub - datitran/jupyter2slides: Cloud Native Presentation Slides with Jupyter Notebook + Reveal.js

Experiments in expressing statistical thinking with interactive design

A visual introduction to probability and statistics.

I have been reading and collecting data science resources for years (back in the days when BI / BA was all the rage). While there are lots of resources on the…

First lecture of MIT course 6.S091: Deep Reinforcement Learning, introducing the fascinating field of Deep RL. For more lecture videos on deep learning, reinforcement learning (RL), artificial intelligence (AI & AGI), and podcast conversations, visit our…

Your daily dose of AI research from AK

Get to know the data structures that you use every day

In this tutorial you will learn how to use Keras for multi-inputs and mixed data. You will train a single end-to-end network capable of handling mixed data, including numerical, categorical, and image data.