Analytics Insight

Best Books to Learn OpenCV in 2026: Top Picks for Beginners

Overview: Seven carefully selected OpenCV books guide beginners from basics to advanced concepts, combining theory, coding ...
Lablab.ai

From Zero to AI Builder with AMD: MI300X GPUs for AI Hackathons

Build AI hackathon projects on AMD MI300X GPUs with $100 in free credits, ROCm open-source stack, and free courses from the ...
marktechpost

Implementing Deep Q-Learning (DQN) from Scratch Using RLax JAX Haiku and Optax to Train a CartPole Reinforcement Learning Agent

In this tutorial, we implement a reinforcement learning agent using RLax, a research-oriented library developed by Google DeepMind for building reinforcement learning algorithms with JAX. We combine ...
Scientific Research Publishing

A Hybrid Deep and Machine Learning Framework with Feature Selection for Automated Classification of Acute Lymphoblastic Leukemia ()

1 Department of Computer Science and Engineering, The People’s University of Bangladesh, Dhaka, Bangladesh. 2 Department of Computer Science and Engineering, Jahangirnagar University, Dhaka, ...
Frontiers

Implementing physics-informed neural networks with deep learning for differential equations

Physics-aware machine learning integrates domain-specific physical knowledge into machine learning models, leading to the development of physics-informed neural networks (PINNs). PINNs embed physical ...
northpennnow

Machine Learning Using Python: A Complete Learning Path With Practical Projects

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...
techannouncer

Discover the Best Python Book PDF for Your Learning Journey

So, you’re looking to learn Python, huh? It’s a pretty popular language, and for good reason. It’s used for all sorts of things, from making websites to crunching numbers. Finding the right book can ...
Hosted on MSN

Deep neural network from scratch in Python – fully connected feedforward tutorial

Learn how to build a fully connected, feedforward deep neural network from scratch in Python! This tutorial covers the theory, forward propagation, backpropagation, and coding step by step for a hands ...
Scientific Research Publishing

Francois Chollet (2021) Deep Learning with Python. Manning Publications.

ABSTRACT: This paper explores the application of various time series prediction models to forecast graphical processing unit (GPU) utilization and power draw for machine learning applications using ...
Microsoft

TorchGeo: Deep Learning With Geospatial Data

Remotely sensed geospatial data are critical for applications including precision agriculture, urban planning, disaster monitoring and response, and climate change research, among others. Deep ...
GitHub

DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research

DR Tulu-8B is the first open Deep Research (DR) model trained for long-form DR tasks. DR Tulu-8B matches OpenAI DR on long-form DR benchmarks. Feburary 9, 2026: 🔥 We released a free interactive demo ...
IEEE

Deep Reinforcement Learning for Distribution System Operations: A Tutorial and Survey

The rapid evolution of modern electric power distribution systems into complex networks of interconnected active devices, distributed generation (DG), and storage poses increasing difficulties for ...