Item Response Theory: Psychometrics meets Data Science with Graded Response Model (GRM)
Author(s): Annette Catherine Paul We have seen a lot of interdisciplinary cross overs with Data Science. This is one of my favorites. Why? The use cases are infinitive as… Continue reading on Towards AI » Published via Towards AI …
HTTP API vs. REST API
Author(s): Michelangiolo Mazzeschi One of the most intricate, yet basics, semantic riddles of computer science Continue reading on Towards AI » Published via Towards AI …
Hypothesis Testing- Test of Mean, Variance, Proportion
Author(s): Indhumathy Chelliah p-value approach, critical value approach, confidence interval approach Continue reading on Towards AI » Published via Towards AI …
How To Perform Letter Recognition in Python Using Random Forest Classifier
Author(s): Ashutosh Malgaonkar Table of Contents: Continue reading on Towards AI » Published via Towards AI …
DropBlock: A New Regularization Technique
Author(s): Renu Khandelwal Explore DropBlock, a new Regularization technique for Convolutional Neural Networks Continue reading on Towards AI » Published via Towards AI …
E-commerce Sales Strategy Using Tableau
Author(s): Juhi Sharma Data Analysis E-commerce Data Analysis Using Tableau Photo by Clay Banks on Unsplash K-mart sales strategy for the year 2020 based on the insights from the sales data in 2019. Introduction Kmart is a leading online retailer in the US and as …
Clustering Custom Data Using the K-Means Algorithm — Python
Author(s): Jayashree domala Machine Learning Clustering Custom Data Using the K-Means Algorithm — Python A guide to understanding and implementing the K-means algorithm using Python. Source: Author What is the K-Means clustering algorithm? The K-Means clustering algorithm is an unsupervised learning algorithm meaning that it …
Building Reinforcement Learning Agents that Learn to Collaborate and Compete at the Same Time
Author(s): Jesus Rodriguez OpenAI has been experimenting with techniques that solve one of the major challenges in reinforcement learning applications. Continue reading on Towards AI » Published via Towards AI …
GPT-3 Explained to a 5-year-old
Author(s): Daksh Trehan Natural Language Processing If you haven’t been paying attention to the wonders of AI, you haven’t been attentive at all! The web has gone crazy over an interactive tool GPT-3. Its use-cases and future possibilities are amazing. (G)enerative (P)retrained (M)odel …
The NLP Cypher | 03.28.21
Author(s): Quantum Stat Couple Gazing at the Moon | Friedrich NATURAL LANGUAGE PROCESSING (NLP) WEEKLY NEWSLETTER A Step Forward in Open Sourcing GPT-3 In the 02.21.21 newsletter, we highlighted EleutherAI’s ambitions for building an open-sourced version of the uber large GPT-3 175B param …
Fully Explained BIRCH Clustering for Outliers with Python
Author(s): Amit Chauhan Unsupervised Learning in clustering to build tree for data Continue reading on Towards AI » Published via Towards AI …
Ensemble Methods Explained in Plain English: Bagging
Author(s): Claudia Ng Understand the intuition behind bagging with examples in Python Continue reading on Towards AI » Published via Towards AI …
Image Intensity Manipulation
Last Updated on March 27, 2021 by Editorial Team Author(s): Akula Hemanth Kumar Computer Vision Photo by Jonathan Bowers on Unsplash What counts as intensity manipulation Explicit changes to pixel values in any of the channels. Mathematical operations on images. Brightness changes. Contrast changes. …
How Can Self-Supervised Models Benefit Different Computer Vision Tasks?
Author(s): Vatsal Saglani SimCLRv2 explained Continue reading on Towards AI » Published via Towards AI …
Facebook AI Learned Object Recognition From 1 Billion Instagram Pics
Author(s): Claire D. Costa SEER: The start of a more powerful, flexible, and accessible era for computer vision Continue reading on Towards AI » Published via Towards AI …
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