AI Vs Machine Learning Vs Deep Learning Vs Generative AI clearly Explained:

Over the past year, I've been compiling some "alchemist's notes" on deep learning. Right now it covers basic optimization, architectures, and generative models. Focus is on learnability -- each page has nice graphics and an end-to-end implementation.

I Created a GitHub Repository to Learn AI Engineering. It contains the best free courses, articles, tutorials, and videos to learn:.- Mathematical Foundations.- AI & ML Fundamentals.- Deep Learning and Specializations.- Generative AI.- Large Language Models (LLMs).- Prompt

Today in the journal Science: BioEmu from Microsoft Research AI for Science. This generative deep learning method emulates protein equilibrium ensembles – key for understanding protein function at scale.

AI Vs Machine Learning Vs Deep Learning Vs Generative AI. 1 - Artificial Intelligence (AI).It is the overarching field focused on creating machines or systems that can perform tasks typically requiring human intelligence, such as reasoning, learning, problem-solving, and

If you want to get into AI Engineering, there are certain skills you'll need. Things like math, machine learning, deep learning, and hands-on engineering experience, to name a few. In this AI Engineering roadmap, @tatevkaren7 covers key statistics, data science, Generative AI,

Intro to Deep Learning and Generative Models course . The Legendary and most practical tutorial on deep learning and concepts of generative models, taught by @rasbt sir . Link in comments 😎👇

The Little Book of Deep Learning!. Probably the best short and concise guide to deep learning available today. It covers everything from core foundations and efficient computation to model architectures, training techniques, and generative AI.

"Intro to Deep Learning and Generative Models ". - 44 hours playlist, taught by legendary @rasbt . - Almost all basic to advanced level topics explained by Sebastian Raschka.

Top 20 Must Know AI Concepts. Machine Learning.Deep Learning.Neural Networks.NLP.Computer Vision.Reinforcement Learning.Generative Models.LLM.Transformers.Feature Engineering.Supervised Learning.Bayesian Learning.Prompt Engineering.AI Agents.Fine Tuning Models.Multimodal Models

Customized design of amorphous solids by generative deep learning. Read more #materials #research #news #TIC2025

FREE Deep Lerning Course from MIT.- Everything you need to know about Deep Learning - from neural networks and CNNs to transformers, reinforcement learning, and generative AI.- 81 lectures covering 7 years of cutting-edge research - Completely free.LINK IN COMMENT

Generative Deep Learning for de Novo Drug Design─A Chemical Space Odyssey #machinelearning #compchem

Replacing numerical simulation with AI models is the goal of PhysicsX. This is the frontier of AI. Believe it or not, engineers and scientists are building Generative and Deep Learning models that will push the boundaries of engineering and science.

Deep Learning for computer vision .Stanford, by Fei-Fei Li et al. great free course that covers all the basics:. - CNNs.- image classification .- neural networks and loss functions.- detection and segmentation.- generative models

In our Artist Highlight series, today we focus on Gene Kogan @genekogan, an artist and former machine learning engineer. After starting his career in music information retrieval, he began exploring generative art through creative coding and deep learning and has helped popularize

Was checking out the free ebook on computer Vision. Solid book covering topics such as:. - Foundations of Vision and Perception.- Image Formation and Processing.- Machine Learning Foundations.- Deep Learning for Vision.- Generative and Probabilistic Models.- Challenges in

#MaterialsScience #AI: researchers have developed a generative deep learning model to generate chemical compositions and crystal structures by from textual descriptions and 3D structural data. The model could help design innovative solid-state batteries -

Al Vs Machine Learning Vs Deep Learning Vs Generative Al. 1 - Artificial Intelligence (AI).It is the overarching field focused on creating machines or systems that can perform tasks typically requiring human intelligence, such as reasoning, learning, problem-solving, and language