30 Best AI Applications Revolutionizing Healthcare, Finance, and Education
30 AI applications in healthcare, finance and education, from AI scribes and fraud models to AI tutors, with trial results, company claims and known risks.
· 19 min read
Machine learning, large language models, AI research, and how AI is applied in industry and work.
30 AI applications in healthcare, finance and education, from AI scribes and fraud models to AI tutors, with trial results, company claims and known risks.
· 19 min read
75 evidence-based examples of AI changing work: productivity trials, entry-level hiring, new roles and skills, AI in hiring, workplace rules and robots.
· 27 min read
40 ways AI is changing business operations, marketing and sales, from support copilots and coding agents to AI search and sales bots, with evidence and risks.
· 19 min read
25 sourced examples of AI changing healthcare, finance, retail, factories, transport, farming, software, law, media and science in 2026, with their limits.
· 19 min read
50 AI use cases in manufacturing, retail and logistics, each with a real deployment, the metrics to track, a maturity rating and the main risk to plan for.
· 23 min read
101 feature engineering techniques with runnable Python: missing values, scaling, encoding, dates, text, location data and leakage-safe feature selection.
· 28 min read
100 machine learning algorithms explained with the core idea, the math, when to use each one, a runnable Python example and a real-world application.
· 71 min read
100 real machine learning applications in healthcare, finance, retail, transport, energy, farming and science, with the methods behind them and their limits.
· 44 min read
100 machine learning datasets for tabular, vision, text, audio, time series, recommender and LLM work, with size, uses, access terms and known pitfalls.
· 41 min read
101 machine learning project ideas from beginner to advanced, each with a public dataset, a baseline to beat, an evaluation plan and a clear definition of done.
· 48 min read
100 runnable scikit-learn examples for classification, regression, text, clustering, anomaly detection, forecasting and recommendations, with real output.
· 18 min read
Sebastian Raschka's newsletter explaining LLM architectures, training methods, and recent machine learning research.
Visit WebsiteAndrej Karpathy's blog on neural networks, deep learning practice, and large language models.
Visit WebsiteResearch write-ups from the Berkeley Artificial Intelligence Research (BAIR) lab at UC Berkeley.
Visit WebsiteEugene Yan's writing on applied machine learning, recommender systems, and building and evaluating LLM products.
Visit WebsiteOfficial blog of Google Research covering new papers, models, and applied machine learning projects.
Visit WebsiteHamel Husain's notes on evaluating and improving LLM applications and practical machine learning engineering.
Visit WebsiteJack Clark's weekly newsletter summarizing notable AI research papers and their policy implications.
Visit WebsiteNathan Lambert's newsletter on language model training, post-training and RLHF, open models, and the AI industry.
Visit WebsiteLilian Weng's long-form technical surveys of machine learning research topics such as LLM agents, diffusion models, and reinforcement learning.
Visit WebsiteSimon Willison's frequently updated weblog on large language models, AI tools, and practical experiments with them.
Visit Website