Deep Learning with Yacine on MSN

Nesterov accelerated gradient (NAG) from scratch in Python – step-by-step tutorial

Dive deep into Nesterov Accelerated Gradient (NAG) and learn how to implement it from scratch in Python. Perfect for ...
Analytics Insight

Best Data Science Courses in India 2026: Top 10 Picks

Overview: Focuses on skills, projects, and AI readiness, not hypeCovers degrees, certificates, and online programmesHelps ...
Deep Learning with Yacine on MSN

Create a perceptron from scratch in Python – step by step tutorial

Learn how to build a perceptron from scratch in Python! This tutorial covers the theory, coding, and practical examples, helping you understand the foundations of neural networks and machine learning.
C&EN

dpdata: A Scalable Python Toolkit for Atomistic Machine Learning Data Sets

School of Artificial Intelligence and Data Science, Unversity of Science and Technology of China, Hefei 230026, P. R. China Suzhou Institute for Advanced Research, University of Science and Technology ...
IEEE

Why Do Machine Learning Notebooks Crash? An Empirical Study on Public Python Jupyter Notebooks

Abstract: Jupyter notebooks have become central in data science, integrating code, text and output in a flexible environment. With the rise of machine learning (ML), notebooks are increasingly used ...
C&EN

Python Library for Monte Carlo Simulations with Ab Initio and Machine-Learned Interatomic Potentials

Dave C. Swalm School of Chemical Engineering and Center for Advanced Vehicular Systems, Mississippi State University, Mississippi State, Mississippi 39762, United States Department of Chemical and ...
tech2geek

Scikit-learn: The Essential Machine Learning Library for Python

If you’re learning machine learning with Python, chances are you’ll come across Scikit-learn. Often described as “Machine Learning in Python,” Scikit-learn is one of the most widely used open-source ...
IEEE

Failure management in optical networks with ML: a tutorial on applications, challenges, and pitfalls [Invited]

Abstract: This tutorial identifies and discusses the main design choices and challenges arising in the application of machine learning (ML) to optical network failure management (ONFM), including ...