Do Not Curse Your Machine Learning Models When They Are Not Performing Well in Real-time — Instead, Do This
Author(s): Suhas Maddali Originally published on Towards AI. While the performance of machine learning models can seem extremely good on the test data, failing to understand the chances of them not performing well on real-time data can cause a lot of loss …
Face Data Augmentation. Part 1: Geometric Transformation
Author(s): Ainur Gainetdinov Originally published on Towards AI. The performance of deep neural nets made a big step forward in the last two decades. Every year new architectures are devised that beat state-of-the-art results. However, only improving architectures won’t work without a …
Galactica: How to (Responsibly) Use the Controversial Language Model Everyone Is Talking About
Author(s): Federico Peccia Originally published on Towards AI. Articles and papers generation Photo by Annie Spratt on Unsplash Perhaps you already read a lot of articles about Galactica, the language model released in November by MetaAI. In the original paper, the authors …
Unleashing the power of WebSockets for real-time Model Inference
Author(s): Vatsal Saglani Originally published on Towards AI. A hands-on guide to serving model inference using sockets GIF by Author A Socket specifies a network address and port via which the application can communicate to the process on the network. Sockets are …
Diffusion Models — my “second?” artist.
Author(s): Albert Nguyen Originally published on Towards AI. Diffusion Models are one of the most popular algorithms in Deep Learning. It is widely used in many applications, such as image generation, object detection, and text-to-image generation. In this article, I will explain …
2022: A Year Full of Amazing AI papers — A Review 🚀
Author(s): Louis Bouchard Originally published on Towards AI. A curated list of the latest breakthroughs in AI by release date with a clear video explanation, link to a more in-depth article, and code. While the world is still recovering, research hasn’t slowed …
How is Google Aiming At a Trillion Parameter Model (PaLM): Page-by-Page Review
Author(s): Dr. Mandar Karhade, MD. PhD. Originally published on Towards AI. PATHWAYS: ASYNCHRONOUS DISTRIBUTED DATAFLOW FOR ML and Scaling Language Modeling with Pathways This time I was going to deviate from a usual 1 paper 1 review approach to 2 papers 1 …
Foundation Models and the Path Towards a Universal Learning Algorithm
Author(s): Jesus Rodriguez Originally published on Towards AI. Can foundation models validate the theory of a master algorithm for all human knowledge? Created with: DALL-E I recently started an AI-focused educational newsletter, that already has over 150,000 subscribers. TheSequence is a no-BS …
How to Anonymize Faces in Images with Deep Learning and Computer Vision
Author(s): Edwin Tan Originally published on Towards AI. Photo by Alexandra Gorn on Unsplash Face blurring is a technique used to anonymize the identity of a person in an image or video by pixelating or covering the face with a blur effect. …
From Garbage In to Gold Out: Understanding Denoising Autoencoders
Author(s): Anay Dongre Originally published on Towards AI. A denoising autoencoder (DAE) is a type of autoencoder neural network architecture that is trained to reconstruct the original input from a corrupted or noisy version of it. Don’t confuse my drawing skills with …
Kickstart Your Data Science Career with this Comprehensive and Easy-to-Follow Roadmap
Author(s): Youssef Hosni Originally published on Towards AI. Table of Contents: Whether you’re a recent graduate or a professional looking to make a career change, the field of Data Science and AI offers a wide range of exciting and lucrative opportunities. In …
This Google Research Provides Improvements in One of the Most Famous Types of Machine Learning Problems
Author(s): Jesus Rodriguez Originally published on Towards AI. Multi-armed bandits are presents across all spectrums of machine learning. Created with Stable Diffusion I recently started an AI-focused educational newsletter, that already has over 150,000 subscribers. TheSequence is a no-BS (meaning no hype, …
Segformer: An Efficient Transformers Design for Semantic Segmentation
Author(s): Albert Nguyen Originally published on Towards AI. Transformers have taken the machine-learning world by storm in the last few years. Their performances surpass state-of-the-art in Natural Language Processing tasks with the self-attention mechanism and even extend the dominance to Computer Vision. …
Mastering 10 Regression Algorithms: A Step-by-Step Practical Approach
Author(s): Fares Sayah Originally published on Towards AI. A Hands-On Guide to Understanding and Evaluating Regression Algorithms Photo by Howie Mapson on Unsplash Linear Regression is one of the simplest algorithms in machine learning. It can be trained using different techniques. In …
Mastering the Fundamentals: Differences Between Sample, Batch, Iteration, And Epoch
Author(s): Clément Delteil Originally published on Towards AI. A Beginner’s Guide to Mastering the Fundamentals of Machine Learning Photo by Robert Ruggiero on Unsplash When you are new to Machine Learning, it is common to get overwhelmed with information. There are so …
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