NLP — Zero to Hero with Python and More!

Last Updated on November 10, 2021 by Editorial Team

Author(s): Towards AI Team

What is new in the AI world, an exciting (and free to access) natural language API, and our monthly editorial picks

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Happy Tuesday, Towards AI family! We have many goodies prepared for you in this edition of the newsletter. We have included some pretty cool and free to access datasets on our machine learning datasets hub — check them out!

Introducing the expert.ai Natural Language API

Add language intelligence to your application right now! Expert.ai Natural Language API provides deep language understanding without any IT infrastructure or installation and scales with your needs so you can start developing intelligent applications today! → Use the API for Free!

NeurIPS, the largest conference in artificial intelligence, is currently underway, and it has over 20k people registered. If you are not registered and would like to access their goodies, please visit this public access version of the NeurIPS website.

If you are into deep learning, we recommend you to check out this phenomenal tutorial by David Duvenaud, Zico Kolter, and Matt Johnson, which makes use of many tools such as Anderson acceleration, differential equations, neural nets, convex optimization, Jax, automatic differentiation and others, presented on NeurIPS.

Next, we recommend you to check out this article titled “We read the paper that forced Timnit Gebru out of Google. Here’s what it says” by Karen Hao from MIT Technology Review, which gives a very insightful overview of what caused the departure of Timtit Gebru, co-lead ethical AI researcher from Google Brain.

For those interested in natural language processing, Carnegie Mellon Professor Graham Neubig just published 23 class-lectures on multilingual natural language processing, including two guest lectures by Pat Littell and Orhan Firat. The video playlist can be accessed for free on Youtube.

Last but not least, Paul Liang and Misha Khodak from ML@CMU published a post containing all of CMU’s submissions to NeurIPS 2020, with many goodies, from papers to code, and much more.

Now into the monthly picks! We pick these articles based on readers, fans, and views a specific piece gets. We hope you enjoy reading them as much as we did. Also, we started doing something new! We will pick our top ten performing articles, and our editors will choose one to two essays that didn’t have outstanding performance, but due to its quality — made the cut for the month.

If you can, please share our subscription link with your friends, colleagues, and acquaintances. We promise we won’t spam their inbox. If you have any feedback regarding our newsletter, please feel free to send us an email.

📚 Editor’s choice featured articles of the month ↓ 📚

NLP — Zero to Hero with Python by Amit Chauhan

Natural Language processing comes under the umbrella of the Artificial Intelligence domain. All computers are good with numerical data to do processing, this class of section deals with text data to analyze different languages in this world. In this article, we will do a morphological study in language processing with python using libraries like Spacy and NLTK…

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Best Laptops for Machine Learning, Data Science, and Deep Learning by Towards AI Team

For the past year, we have looked at over 2,000 laptops [8] and picked what we consider to be the best laptops for machine learning, data science, and deep learning for every budget — future proof your AI rig! Machine learners, deep learning practitioners, and data scientists are continually looking for the edge on their performance-oriented devices. That’s why we looked at over 2,000 laptops to bring you what we consider the best laptops for your projects on machine learning, deep learning, and data science.

[ Read More ]

The Deep Learning Tool We Wish We Had In Grad School by Angela Jiang and Liam Li

Machine learning Ph.D. students are in a unique position: they often need to run large-scale experiments to conduct state-of-the-art research, but they don’t have the support of the platform teams that industrial ML engineers can rely on. As a result, Ph.D. students waste countless hours writing boilerplate code, ad-hoc scripts and hacking together infrastructure — rather than doing research. As former Ph.D. students ourselves, we recount our hands-on experience with these challenges and explain how open-source tools like Determined would have made grad school a lot less painful.

[ Read More ]

Timeline for Data Science Competence by Benjamin Obi Tayo Ph.D.

For anyone interested in jumping into the field of data science, one of the most important questions to ask is: How long does it take to gain competency in data science? This article will discuss the typical timeline for data science competency. The time required to gain competency in data science depends on the level of competency. In Section II, we will discuss the three levels of data science. In Section III, we discuss the time required for gaining data science competency based on the level of interest. A short summary completes the article…

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Getting Valuable Insights and Visualizations from Tweets Using Python and Twint by Zijing Zhu

Recently I got myself obsessed with a Japanese tv show. I found myself cannot stop checking on Twitter, Instagram, and a Chinese app called Douban for updates and discussions about the show. In the meantime, I ran into an introduction article about the Python library Twint, which is very convenient in gathering twitter data. While it is torturing waiting for the new episode to come out every week, I decided to use the waiting time exploring Twint and derive some insights about the show from Twitter.

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7 Things I Learned During My 2 Years in an AI Startup by Arunn Thevapalan

I recall the day when I was offered my first data science job. Up until then, it was mostly me learning through online courses and working on portfolio projects. On my way back home after bagging the offer, I was punching in the air and patting myself on the back for my achievement. Breaking into the world of data science as a fresher isn’t easy and is definitely an achievement. Years have passed since then. As I move into bigger challenges in my career, here’s me reflecting upon my experience and, more importantly, sharing the learnings as a Machine Learning Engineer in an AI startup for the past 2+ years.

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Analyzing The Presidential Debates by Lawrence Alaso Krukrubo

Exploring Sentiments, Key-Phrase-Extraction, and Inferences … 2020 has been one ‘hell-of-a-year,’ and we’re about the eleventh month. It’s that time again for Americans to take to the polls. If you’ve lived long enough, you recognize the patterns…Each opposing political side shades the other, scandals and leaks may pop, shortcomings are magnified, critics make the news, promises are doled out ‘rather-convincingly,’ and there’s an overwhelming sense of ‘nationality and togetherness’ touted by both sides…

[ Read More ]

This AI can Colorize your Black & White Photos with Full Photorealistic Renders! (DeOldify) by Louis (What’s AI) Bouchard

DeOldify is a technique to colorize and restore old black and white images or even film footage. It was developed and is still getting updated by only one person Jason Antic. It is now the state of the art way to colorize black and white images, and everything is open-sourced, but we will get back to this in a bit. First, let’s see how he achieved that. It uses a new type of GAN training method called NoGAN that he developed himself to solve the main problems that appeared when training using a normal adversarial network architecture composed of…

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How to get a Data Science Job without Experience by George Pipis

Let’s assume that you are a candidate who has recently graduated from the University holding a BSc/MSc degree in Mathematics, Computer Science, Engineering, or other related fields, and you would like to start a career as Data Scientist. The grades and the University degree indicate your theoretical background and your ability to learn new things. However, in the real world, things are different from the University, not necessarily more difficult, and somehow the hiring managers would like to know more about you and especially the way that you work…

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11 Great Youtube Channels To Learn Python Programming for Free by Jair Ribeiro

If you are looking for the best Youtube channels to dig into Python programming and learn from the best, you have a great list with 21 (my lucky number) amazing programmers who share tips and secrets that will help you to become a master!

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Dear Hiring Manager, Please Stop Using Take-Home Assignments! by Marie Stephen Leo

Data Science and Data Analytics are some of the hottest jobs on the market going into 2021. The field is so popular and job descriptions so broad that most job openings receive hundreds or even thousands of applicants because most men know they can apply to a position even when they don’t meet 100% of the requirements. For some reason…

[ Read More ]

10 Game-changing AI Breakthroughs Worth Knowing About by Nishu Jain

From the beginning of my AI journey, I found several ideas and concepts promising unparalleled potential; Pieces of research and development that were mind-blowing; And breakthroughs that pushed this field forward, leaving their mark on its glorious history. Also, in the last few years, the number of people pointing to the “Skynet-terminator” scenario has increased exponentially …

[ Read More ]

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NLP — Zero to Hero with Python and More! was originally published in Towards AI on Medium, where people are continuing the conversation by highlighting and responding to this story.

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