Introduction to Image Processing with Python
Author(s): Erika Lacson Originally published on Towards AI. Episode 2: Image Enhancements, Part 3: Histogram Manipulation Histogram Manipulation Techniques. Photo by Author Welcome back to the third part of the second episode of our image processing series! In the previous parts of …
Introduction to Image Processing with Python
Author(s): Erika Lacson Originally published on Towards AI. Episode 2: Image Enhancements, Part 3: Histogram Manipulation Histogram Manipulation Techniques. Photo by Author Welcome back to the third part of the second episode of our image processing series! In the previous parts of …
Building Your Own Songwriter: Write a Song Like Ed-Sheeran With nanoGPT
Author(s): Lan Chu Originally published on Towards AI. Quickly train a baby GPT to generate Ed Sheeran-style music. Ed Sheeran teaching baby GPT how to compose cheesy love songs. Image generated with Dall-E 2. Recently I watched the tutorial Let’s build GPT: …
How Much AI is in the Apple Vision Pro?
Author(s): Rafe Brena, Ph.D. Originally published on Towards AI. Not enough AI yet Photo by Sumudu Mohottige on Unsplash At this point, it’s hard not to be aware of the Apple Vision Pro, a new-of-its-kind AR and VR device announced by Apple …
Exogenous Variables in Time Series Forecasting with Facebook Prophet
Author(s): David Andres Originally published on Towards AI. Photo by John Fowler on Unsplash In the previous part of our Facebook Prophet series, we covered how to model the seasonality component. You should also recall the first part, in which we dealt …
Let’s Do: Time Series Decomposition
Author(s): Bradley Stephen Shaw Originally published on Towards AI. What makes your time series tick? There’s only one way to find out — by taking it apart. Photo by Sean Whelan on Unsplash Time series are quite possibly the most ubiquitous collections …
5 Powerful Cross-Validation Methods to Skyrocket Robustness of Your ML Models
Author(s): Bex T. Originally published on Towards AI. All CV procedures you need to know as a data scientist, explained Image by me with Midjourney Before I start selling the merchandise, I need to pitch the main idea. Picture a crazy world …
Managing an AI developer: Lessons Learned from SMOL AI — Part 1
Author(s): Meir Kanevskiy Originally published on Towards AI. Source: Image by DALL-E One of the most interesting ramifications of the recent breakthroughs, specifically in large language models, is the potential for building automated agents capable of fulfilling work projects using these models. …
The future of Artificial Intelligence is Open-source! Here’s why?
Author(s): Janik and Patrick Tinz Originally published on Towards AI. Open-source AI gets Big Tech in trouble Photo by Tim Mossholder on Unsplash Developments in open-source artificial intelligence (AI) have accelerated massively in the last three months. So it stands to reason …
Decoding the Binomial Distribution: A Fundamental Concept for Data Scientists
Author(s): Egor Howell Originally published on Towards AI. Understanding the basic building blocks of the binomial distribution Photo by Chris Briggs on Unsplash The binomial distribution is a widely used statistical distribution that Data Scientists should be familiar with, as it appears …
19 Most Elegant Sklearn Tricks I Found After 3 Years of Use
Author(s): Bex T. Originally published on Towards AI. Advanced techniques and hidden gems for effective machine learning Learn about 19 Sklearn features you have never seen that are direct and elegant replacements to common operations you do manually. Image by me with …
Bagging vs. Boosting: The Power of Ensemble Methods in Machine Learning
Author(s): Thomas A Dorfer Originally published on Towards AI. How to maximize predictive performance by creating a strong learner from multiple weak ones Image by the Author. Complex problems are rarely solved through singular thought or action. A collective weather forecast produced …
Correct Handling of Outliers to Improve Overfitting Scenarios
Author(s): Kayenga Campos Originally published on Towards AI. Correct Handling of Outliers to Improve Overfitting Scenarios Look how quantile treatment of outliers can improve model accuracy The main approach of machine learning consists of splitting the data into training and testing sets. …
Explaining Hypothesis Testing to a High School Student — Part 1
Author(s): Anmol Tomar Originally published on Towards AI. An Intuition Image by Author In the realm of data science, hypothesis testing holds immense significance as a powerful tool for making informed decisions based on observed data. By systematically examining assumptions and evaluating …
OpenAI Just Introduced Function Callings Feature: Everything You Need to Know
Author(s): Youssef Hosni Originally published on Towards AI. The Most Powerful Update to Their API Since Its Release OpenAI has released new updates to its API and they are astonishing. The most important one of them is the function calling feature. Using …
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