Ultimate Guide to Natural Language Processing Courses

Ultimate Guide to Natural Language Processing Courses

  • May 11, 2020
Table of Contents

Ultimate Guide to Natural Language Processing Courses

Selecting an online course that will match your requirements is very frustrating if you have high standards. Most of them are not comprehensive and a lot of time spent on them is wasted. How would you feel, if someone would provide you a critical path and tell, what modules exactly and in which order will provide you comprehensive, expert-level knowledge?

Awesome. That is why I am going to help you with this guide to selecting a Natural Language Processing course, utilizing my 8 years of practical experience in Machine Learning. I’ve personally completed or skimmed over the 15 most popular courses.

In my rigorous review, I focus on the practical and business knowledge that they provide. This article was thought in the way that it will provide great value whether you are just starting your journey with NLP or thinking how to implement modern algorithms into your business model. Take a look at the Critical Path and pick modules that you are interested in the most.

Source: airev.us

Tags :
Share :
comments powered by Disqus

Related Posts

The Dark Secrets Of BERT

The Dark Secrets Of BERT

BERT stands for Bidirectional Encoder Representations from Transformers. This model is basically a multi-layer bidirectional Transformer encoder(Devlin, Chang, Lee, & Toutanova, 2019), and there are multiple excellent guides about how it works generally, includingthe Illustrated Transformer. What we focus on is one specific component of Transformer architecture known as self-attention.

Read More
The Best NLP Papers From ICLR 2020

The Best NLP Papers From ICLR 2020

I went through 687 papers that were accepted to ICLR 2020 virtual conference (out of 2594 submitted – up 63% since 2019!) and identified 9 papers with the potential to advance the use of deep learning NLP models in everyday use cases.

Read More
A Hacker’s Guide to Efficiently Train Deep Learning Models

A Hacker’s Guide to Efficiently Train Deep Learning Models

Three months ago, I participated in a data science challenge that took place at my company. The goal was to help a marine researcher better identify whales based on the appearance of their flukes. More specifically, we were asked to predict for each image of a test set, the top 20 most similar images from the full database (train+test).

Read More