Data-Centric AI β Data Collection and Augmentation Strategy
Author(s): Tan Pengshi Alvin Originally published on Towards AI. A comprehensive guide to data generation strategy for data-centric Machine Learning projects Image by Dave Photoz on Unsplash In the world of deep learning, complex models are data-hungry β in both quality and …
Pandas Cheat Sheet: Functions for Data Analysis
Author(s): Gencay I. Originally published on Towards AI. Pandas Coding Examples for Efficient Data Manipulation and Analysis in Python Image by Author It is no secret that data is the lifeblood of modern business, and the ability to manipulate and analyze data …
Marketing Measurement-1: The Intuition Behind Incrementality
Author(s): Deepak Chopra | Talking Data Science Originally published on Towards AI. Top highlight Photo by Jason Dent on Unsplash For marketers, analysts, or data scientists β marketing measurement is one of the oldest problems to have existed since the inception of …
Rustic Learning: Machine Learning in Rust β Part 1: Introduction to Rust
Author(s): Ulrik Thyge Pedersen Originally published on Towards AI. An Introduction to the Fundamentals of the programming language Rust Photo by ZdenΔk MachΓ‘Δek on Unsplash Rustic Learning is a series of articles that explores the use of Rust programming language for machine …
Stacking and Splitting NumPy Arrays Like a Pro: Part 2
Author(s): Devansh Sheth Originally published on Towards AI. Read this guide and split those NumPy arrays like a Ninja! Photo by Krys Amon on Unsplash NumPy is one of the most important libraries for Data Science and working with numerical data. Mastering …
How to Use Poisson Distribution to Predict Match Scores with Python
Author(s): Gencay I. Originally published on Towards AI. Using Poisson Distribution for Accurate Match Score Prediction in Python Image by Author Yesterday, I watched a match between my favorite football team and another team. At the beginning of the game, I had …
Rustic Learning: Machine Learning in Rust β Part 3: Deep Learning Bindings
Author(s): Ulrik Thyge Pedersen Originally published on Towards AI. An Introduction to Neural Network Bindings in Rust Photo by Jay Heike on Unsplash Rustic Learning is a series of articles that explores the use of Rust programming language for machine learning tasks. …
Unveiling and Addressing Bias in Natural Language Processing
Author(s): Yunzhe Wang Originally published on Towards AI. Understanding and mitigating bias in word embeddings and their implications on AI fairness image by Midjourney The rapid growth of artificial intelligence (AI) and natural language processing (NLP) in recent years has transformed various …
Rustic Learning: Machine Learning in Rust β Part 4: Neural Networks
Author(s): Ulrik Thyge Pedersen Originally published on Towards AI. An Introduction to Rust Native Neural Networks Photo by Beth Macdonald on Unsplash Rustic Learning is a series of articles that explores the use of Rust programming language for machine learning tasks. The …
Rustic Learning: Machine Learning in Rust β Part 5: Model Deployment
Author(s): Ulrik Thyge Pedersen Originally published on Towards AI. An Introduction to Rustβs Deployment of ML Models Photo by david Griffiths on Unsplash Rustic Learning is a series of articles that explores the use of Rust programming language for machine learning tasks. …
Uncovering the Art of Combat: A Data Scientistβs Exploration of Mixed Martial Arts
Author(s): John Adeojo Originally published on Towards AI. Examining the Impact of Fighting Styles on MMA Matchups with Machine Learning & Statistical Analysis Image by Author: Generated with Midjourney prompt βThe Stance Standoff, 2023 β A captivating and intense photograph capturing the …
History of AI: Maturation of Artificial Intelligence (1943β1952)
Author(s): Dr. Mandar Karhade, MD. PhD. Originally published on Towards AI. The period from 1943 to 1952 is considered the maturation period of AI, as several important breakthroughs were made during this time. Artificial Intelligence has rapidly become one of the most …
From Pre-RNNs to GPT-4: How Large Language Models are Changing NLP
Author(s): Hitesh Hinduja Originally published on Towards AI. Introduction Large Language Models (LLMs) are currently a popular topic of discussion across various social media platforms such as LinkedIn and Twitter. Their prevalence is evident from the fact that ChatGPT has already made …
![Building and Deploying a GAN Streamlit Web App on Heroku [Part 1]](https://i3.wp.com/miro.medium.com/v2/resize:fit:875/0*kCp27RZLiC9Amiv8.png?w=875&resize=875,368&ssl=1 "Building and Deploying a GAN Streamlit Web App on Heroku [Part 1]")
Building and Deploying a GAN Streamlit Web App on Heroku [Part 1]
Author(s): Youssef Hosni Originally published on Towards AI. Table of Content: Generative Adversarial Networks (GANs) are a type of deep learning architecture that has become increasingly popular for generating new and realistic data, such as images, videos, and audio. Building a GAN …
Why Strategic Plans Arenβt the Best Plan For Data Science
Author(s): Jonathan Burley Originally published on Towards AI. Tech and data science winners treat strategy differently Data Science as an exercise in building new products and companies retains the same pitfalls as any other business process before it: clinging to old, formerly …
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