Probability Theory: Explaining Prediction of Uncertainty
Author(s): Abhijith S Babu Originally published on Towards AI. Our future, as we all know, is uncertain. Using the techniques available right now, it is nearly impossible to predict the future. But we still make plans for the future, assuming things will …
Why Open Source Models May Not Win The AI Race
Author(s): Assaf Elovic Originally published on Towards AI. And Why Incumbents like Google, Facebook, and Microsoft Still Hold the Throne The rapid progress in open-source models has given rise to the belief that these models could pose a significant challenge to incumbent …
Meet GPTCache: A New Framework that Brings Caching to LLM Applications
Author(s): Jesus Rodriguez Originally published on Towards AI. GPTCache expands on the ideas of LLM memory by providing a general-purpose framework to store information in LLM workflows. Created Using Midjourney I recently started an AI-focused educational newsletter, that already has over 160,000 …
The Secret Python Skills That Separate Good Data Scientists from Great Ones
Author(s): Gencay I. Originally published on Towards AI. Conclusion Created in LeonardoAI In the fascinating realm of Data Science and Machine Learning, proficiency in Python has emerged as an invaluable skill. Beyond a solid understanding of Python, mastering certain Python abilities can …
Approximate Nearest Neighbors
Author(s): Harshit Sharma Originally published on Towards AI. And where to find them using Product Quantization You must have heard of KNN (k-Nearest Neighbors) and the fact that it is as easy as it gets when retrieving the most similar items to …
20 Most Elegant NumPy Tricks I Found After 3 Years of Use
Author(s): Bex T. Originally published on Towards AI. Become a NumPy samurai Image by me with Midjourney Every data scientist admires someone. For some, it might be people who create killer data visualizations; for others, it is simply anyone who answers their …
How does Active Learning Work?
Author(s): Louis Bouchard Originally published on Towards AI. Active learning explained in 5 minutes Originally published on louisbouchard.ai, read it 2 days before on my blog! We now deal with immense amounts of data thanks to the superpowers of large models, including …
Meet I-JEPA: Meta AI’s First Super Model Based on their Theory of Autonomous Intelligence
Author(s): Jesus Rodriguez Originally published on Towards AI. The new model is able to make predictions based on abstract predictions instead of pixel-level detail. Created Using Midjourney I recently started an AI-focused educational newsletter, that already has over 160,000 subscribers. TheSequence is …
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 …
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. …
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