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12 teachers

Machine learning Clear all

Nadia Haddad

Practical NLP: from tokens and embeddings to classification, translation and speechtokenisation, embeddings, text classification9 tutors4.5(22)Sample

Lukas Brenner

Model evaluation you can trust: splits, metrics, leakage and tuningtrain validation test splits, cross validation, overfitting9 tutors4.5(22)Sample

Kojo Amankwah

Experiments, causal questions and responsible models, explained for decision makersA/B testing, experiment design, statistical power9 tutors4.5(23)Sample

Lin Zhao

Data cleaning, SQL, exploratory analysis and honest chartsdata cleaning, exploratory data analysis, SQL9 tutors4.5(22)Sample

Mira Okafor

I teach how neural networks learn, one small worked example at a timeneural network fundamentals, activation and loss functions, backpropagation9 tutors4.5(21)Sample

Kavya Raman

Classical machine learning models, worked through on paper before any codelinear and logistic regression, decision trees, random forests9 tutors4.4(20)Sample

Nikolai Sorin

Architectures explained from the inside: convolutions, recurrence, attention and beyondconvolutional networks, recurrent networks, transformers9 tutors4.6(22)Sample

Kenta Arai

Probability for machine learning, plus forecasting and anomaly detectionprobability, expectation and variance, maximum likelihood9 tutors4.4(18)Sample

Katarzyna Wolska

Linear algebra for AI, with geometry first and notation secondvectors, matrices, dot products9 tutors4.6(21)Sample

Leandro Ferraz

Calculus and optimisation for machine learning, done by handderivatives, gradients, chain rule9 tutors4.6(18)Sample

Yohannes Tesfaye

Machine learning engineer who runs portfolio reviews and mock interviews for technical AI rolesML engineering interviews, data science interviews, AI product manager interviews9 tutors4.5(17)Sample

Daniel Reyes

Teaches machine learning, Python and AI agentsMachine learning fundamentals, Python, tool calling and AI agents3 tutorsNew