Word-Level Text Generation
Author(s): George Pipis A practical example of Word Level Text Generation with Tensorflow Continue reading on Towards AI » Published via Towards AI …
What is Lobe and how is Microsoft Trying to Make AI mainstream?
Author(s): Jair Ribeiro Microsoft released a free public preview of a tool that lets people train AI models without writing a single line of code. Continue reading on Towards AI » Published via Towards AI …
Imbalanced-learn: Handling imbalanced class problem
Author(s): Chetan Ambi A hands-on guide for handling imbalanced data using imbalanced-learn Continue reading on Towards AI » Published via Towards AI …
Google Colab 101 Tutorial with Python — Tips, Tricks, and FAQ
Author(s): Saniya Parveez, Roberto Iriondo Source: Derivative from original by Bongkarn Thanyakij on Pexels An in-depth tutorial on how to use Google Colab with Python, along with Colab’s tips, tricks, and FAQ This tutorial’s code is available on Github and its full implementation as …
K-Means Simplified
Author(s): Luthfi Ramadhan Data Science, Machine Learning Short Introduction and Numerical Example of K-Means Clustering Source: http://graphalchemist.github.io/Alchemy/images/features/cluster_team.png What is clustering? Clustering is the process of grouping a set of data objects (or observations) into subsets. Each subset is a cluster, such that objects …
Develop Text into WordCloud in Python
Author(s): Amit Chauhan Representation of text data Visualization Continue reading on Towards AI » Published via Towards AI …
Python Fire
Author(s): Bala Priya C Programming Understanding Fire- a command-line interface generation library Photo by Maxwell Nelson on Unsplash This blog post summarizes the use cases of Python Fire, explained by David Bieber, a Software Engineer at Google Brain in a webinar organized by …
Build Your own Recommendation Engine-Netflix Demystified: Demo+Code
Author(s): Ravi Shankar An intro to recommender systems with live implementation What should I watch this evening? How often you feel after a hectic day at work that what should I watch next? As for me — yes, and more than once. …
Truth = Utility
Author(s): Naim Kabir Definition and implications of a new kind of epistemology Continue reading on Towards AI » Published via Towards AI …
Everyone Can Understand Machine Learning — Naive Bayes Classification
Author(s): Christopher Tao Let the algorithm guessing the sex of a person Continue reading on Towards AI » Published via Towards AI …
Read a CSV File from the Internet Directly Into Your Code
Author(s): Benjamin Obi Tayo Ph.D. Use functions such as download.file(), read.csv() and pd.read_csv() to read a CSV file from the internet directly into your R or Python… Continue reading on Towards AI » Published via Towards AI …
How to Apply Text Distances and Fuzzy Joins
Author(s): George Pipis A walk-through example of Text Distances and Fuzzy Joins in R Continue reading on Towards AI » Published via Towards AI …
Your Data Science Toolbox — What is Inside?
Author(s): Benjamin Obi Tayo Ph.D. As a data scientist, you can only perform tasks which you have the right tools for Continue reading on Towards AI » Published via Towards AI …
Heart Disease Prediction using Machine Learning with Python
Author(s): Amit Chauhan Machine Learning approaches to classifying heart disease or not. Continue reading on Towards AI » Published via Towards AI …
Bayesian Updating and the “Picture Becomes Clearer” Analogy
Author(s): David Aldous, Ph.D. Bayesian updating — revising an estimate when new information is available — is a key concept in data science. It seems intuitively obvious that (within an accurate probability model of a real-world phenomenon) the revised estimate will typically …
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