21 Words About Knowledge, Every AI-Savvy Leader Must Know
Author(s): Yannique Hecht Originally published on Towards AI. Artificial Intelligence Think you can explain these? Put your knowledge to the test! [This is the 2nd part of a series. Make sure you read about Search Algorithms before continuing. Future topics include Uncertainty, …
Deep Learning in Enterprise for Team Members
Author(s): Ali S. Razavian Originally published on Towards AI. Deep Learning Photo by John Schnobrich on Unsplash In this article, I’m trying to address some of the strategic mistakes that development teams do in industry and try to come up with a …
What? How? Why? — In the World of Data Science!
Author(s): Deepak Sekar Originally published on Towards AI. In this article, we will see the three things that matter the most in the Data Science Process What — What is the Business requirement? What are the data sources and features? What is …
Linear Regression from Scratch
Author(s): Nunzio Logallo Originally published on Towards AI. Photo by William Daigneault on Unsplash If you started to learn data science or machine learning, you have also heard about linear regression, but what is it and when should we use it? Linear …
NLP Colab Repository
Author(s): Ricky Costa Originally published on Towards AI. Photo by rolf neumann on Unsplash More than 100 Colab Notebooks Running AI Models In January, we released the Big Bad NLP Database to help ML developers get exposed to quality and diverse datasets. …
Predicting Sales using R programming
Author(s): Suyash Maheshwari Originally published on Towards AI. In this article, I will forecast the sales of a multinational retail corporation. The dataset for this can be found on Kaggle. We have been provided with weekly sales data on which we train …
How and Why to Implement Stemming and Lemmatization from NLTK
Author(s): Manmohan Singh Originally published on Towards AI. In this article, we try to solve one of NLP’s problems by implementing Stemming and Lemmatization Source: pixxabay.com The English language has more than a million words in its vocabulary. Around 170k are in …
5 Different Ways to Build ML Models!
Author(s): Deepak Sekar Originally published on Towards AI. We have come across data science platforms and ML offerings targeted for expert audiences who have Python/ R/ Matlab..etc skills and who understand algorithms/ kernels..etc. But, what if people who understand data very well …
NLP News Cypher | 04.19.20
Author(s): Ricky Costa Originally published on Towards AI. Photo by Pawel Nolbert on Unsplash NATURAL LANGUAGE PROCESSING (NLP) WEEKLY NEWSLETTER NLP News Cypher U+007C 04.19.20 Parallels The universe runs on a simple rule, and it could be, that the framework of this …
Mismatch Between Academic and Real-world Data Science Projects
Author(s): Benjamin Obi Tayo Ph.D. Originally published on Towards AI. Capstone projects in academic data science training should be a semester or two long, and should prioritize group projects over individual projects Photo by Mimi Thian on Unsplash Academic data science programs …
Checking the Sentiment of a Tweet Using Machine Learning
Author(s): Saikat Biswas Originally published on Towards AI. Image Source: Unsplash Let’s see some tweets and classify them as positive or negative sentiment When we hear the word Twitter, what does it ring to our ears? Well, for some, its a source …
Meta-Learning in NLP Classification
Author(s): Edward Ma Originally published on Towards AI. Learning to learn Unlike well-known dataset, our real life problem domain always only have small labeled dataset while we may not able to train a good model under this scenario. Data augmentation is one …
12 Free NLP Datasets to Work on to Tide you Through this Pandemic
Author(s): Timothy Tan Originally published on Towards AI. Photo by Luke Chesser on Unsplash You probably have seen how fast COVID-19 spreads if it left unchecked. As much as we all want our normal lives back again, the best thing we can …
Introduction to the Pandas Library
Author(s): Saiteja Kura Originally published on Towards AI. Source — Nimble Coding Before beginning, I would suggest you read my previous article on NumPy here. Although NumPy’s arrays are better than Python’s data structures several limitations hinder its usage.1. NumPy’s high dimensional …
Implementation of Principal Component Analysis from scratch
Author(s): Navoneel Chakrabarty Originally published on Towards AI. Let’s Get Started Real-time data may have a vast number of attributes, which often makes essential Exploratory Data Analytics very difficult. Such data are known as highly Multi-Dimensional Data in which each and every …
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