Foundations

ML Fundamentals

Neural networks, backpropagation, gradient descent โ€” the maths behind AI

13180
lessons
Skills in this topic
View full skill map โ†’
ML Maths Basics
beginner
Manipulate vectors and matrices
Supervised Learning
beginner
Train decision trees, random forests, and neural nets
Unsupervised Learning
intermediate
Apply k-means and DBSCAN clustering
ML Pipelines
intermediate
Engineer features and handle missing data
Pistol Squat Progression with Mandy + ๐Ÿฆ—
ML Fundamentals
Pistol Squat Progression with Mandy + ๐Ÿฆ—
deeplizard Beginner 2y ago
Maximizing the Potential of Deep Learning in Tabular Data Analysis // Sachin Abeywardana //#180 clip
ML Fundamentals
Maximizing the Potential of Deep Learning in Tabular Data Analysis // Sachin Abeywardana //#180 clip
MLOps.community Beginner 2y ago
Finetuning Open-Source LLMs // Sebastian Raschka // LLMs in Production Conference 3 Keynote 1
ML Fundamentals
Finetuning Open-Source LLMs // Sebastian Raschka // LLMs in Production Conference 3 Keynote 1
MLOps.community Beginner 2y ago
Building a GenAI Ready ML Platform with Metaflow at Autodesk
ML Fundamentals
Building a GenAI Ready ML Platform with Metaflow at Autodesk
Outerbounds Beginner 2y ago
Different Front- end Full- Stack Technologies Free Webinar
ML Fundamentals
Different Front- end Full- Stack Technologies Free Webinar
Entri Coding เดฎเดฒเดฏเดพเดณเด‚ Beginner 2y ago
Stanford CS109 I Algorithmic Analysis I 2022 I Lecture 20
ML Fundamentals
Stanford CS109 I Algorithmic Analysis I 2022 I Lecture 20
Stanford Online Beginner 2y ago
Stanford CS109 I Future of Probability I 2022 I Lecture 28
ML Fundamentals
Stanford CS109 I Future of Probability I 2022 I Lecture 28
Stanford Online Beginner 2y ago
Raw Conversation-What Does Machine Learning Engineer do?
ML Fundamentals
Raw Conversation-What Does Machine Learning Engineer do?
Krish Naik Beginner 2y ago
3 3 surprising, high paying jobs that donโ€™t need a degree!
ML Fundamentals
3 3 surprising, high paying jobs that donโ€™t need a degree!
Coursera Beginner 2y ago
Quad Flexibility with Mandy + Lizard ๐ŸฆŽ๐Ÿ’ช
ML Fundamentals
Quad Flexibility with Mandy + Lizard ๐ŸฆŽ๐Ÿ’ช
deeplizard Beginner 2y ago
What are Decision Trees?
ML Fundamentals
What are Decision Trees?
TensorFlow Beginner 2y ago
I Day Traded $1000 Using Reinforcement Learning and Bayesian Statistics
ML Fundamentals
I Day Traded $1000 Using Reinforcement Learning and Bayesian Statistics
ritvikmath Beginner 2y ago
How to solve problems with Reinforcement Learning | Markov Decision Process
ML Fundamentals
How to solve problems with Reinforcement Learning | Markov Decision Process
CodeEmporium Advanced 2y ago
Live Q&A After Long Time- Krish Naik
ML Fundamentals
Live Q&A After Long Time- Krish Naik
Krish Naik Beginner 2y ago
The Pirate Bay Saga PART- 1
ML Fundamentals
The Pirate Bay Saga PART- 1
Entri Coding เดฎเดฒเดฏเดพเดณเด‚ Beginner 2y ago
In demand careers you should know about: Bookkeeping
ML Fundamentals
In demand careers you should know about: Bookkeeping
Coursera Beginner 2y ago
Mechanical Engineer to Deep Learning Engineer with 2X Salary!
ML Fundamentals
Mechanical Engineer to Deep Learning Engineer with 2X Salary!
codebasics Beginner 2y ago
Oblivious Transfer - Computerphile
ML Fundamentals
Oblivious Transfer - Computerphile
Computerphile Beginner 2y ago
LSTM Explained | Introduction to LSTM | Deep Learning Training | Edureka Rewind
ML Fundamentals
LSTM Explained | Introduction to LSTM | Deep Learning Training | Edureka Rewind
edureka! Beginner 2y ago
Stanford CS109 I Advanced Probability I 2022 I Lecture 27
ML Fundamentals
Stanford CS109 I Advanced Probability I 2022 I Lecture 27
Stanford Online Beginner 2y ago
Stanford CS109 I Deep Learning I 2022 I Lecture 25
ML Fundamentals
Stanford CS109 I Deep Learning I 2022 I Lecture 25
Stanford Online Beginner 2y ago
Stanford CS109 I Central Limit Theorem I 2022 I Lecture 18
ML Fundamentals
Stanford CS109 I Central Limit Theorem I 2022 I Lecture 18
Stanford Online Beginner 2y ago
Get started TODAY!
ML Fundamentals
Get started TODAY!
Coursera Beginner 2y ago
Complete ML,DL,NLP And Computer Vision Project Guide With Free Videos And Materials
ML Fundamentals
Complete ML,DL,NLP And Computer Vision Project Guide With Free Videos And Materials
Krish Naik Beginner 2y ago
Stanford Seminar - Perception-Rich Robot Autonomy with Neural Environment Models
ML Fundamentals
Stanford Seminar - Perception-Rich Robot Autonomy with Neural Environment Models
Stanford Online Beginner 2y ago
Want a career that's always in demand?
ML Fundamentals
Want a career that's always in demand?
Coursera Intermediate 2y ago
Stanford CS109 Probability for Computer Scientists I Logistic Regression I 2022 I Lecture 24
ML Fundamentals
Stanford CS109 Probability for Computer Scientists I Logistic Regression I 2022 I Lecture 24
Stanford Online Beginner 2y ago
Stanford CS109 Probability for Computer Scientists I Naive Bayes I 2022 I Lecture 23
ML Fundamentals
Stanford CS109 Probability for Computer Scientists I Naive Bayes I 2022 I Lecture 23
Stanford Online Beginner 2y ago
Stanford CS109 Probability for Computer Scientists I  M.A.P. I 2022 I Lecture 22
ML Fundamentals
Stanford CS109 Probability for Computer Scientists I M.A.P. I 2022 I Lecture 22
Stanford Online Beginner 2y ago
Stanford CS109 Probability for Computer Scientists I M.L.E. I 2022 I Lecture 21
ML Fundamentals
Stanford CS109 Probability for Computer Scientists I M.L.E. I 2022 I Lecture 21
Stanford Online Beginner 2y ago
Stanford CS109 Probability for Computer Scientists I Adding Random Variables I 2022 I Lecture 17
ML Fundamentals
Stanford CS109 Probability for Computer Scientists I Adding Random Variables I 2022 I Lecture 17
Stanford Online Beginner 2y ago
Stanford CS109 Probability for Computer Scientists I Beta I 2022 I Lecture 16
ML Fundamentals
Stanford CS109 Probability for Computer Scientists I Beta I 2022 I Lecture 16
Stanford Online Beginner 2y ago
Stanford CS109 Probability for Computer Scientists I General Inference I 2022 I Lecture 15
ML Fundamentals
Stanford CS109 Probability for Computer Scientists I General Inference I 2022 I Lecture 15
Stanford Online Beginner 2y ago
Stanford CS109 Probability for Computer Scientists I Modelling I 2022 I Lecture 14
ML Fundamentals
Stanford CS109 Probability for Computer Scientists I Modelling I 2022 I Lecture 14
Stanford Online Beginner 2y ago
Stanford CS109 Probability for Computer Scientists I Inference II I 2022 I Lecture 13
ML Fundamentals
Stanford CS109 Probability for Computer Scientists I Inference II I 2022 I Lecture 13
Stanford Online Beginner 2y ago
Stanford CS109 Probability for Computer Scientists I Inference I 2022 I Lecture 12
ML Fundamentals
Stanford CS109 Probability for Computer Scientists I Inference I 2022 I Lecture 12
Stanford Online Beginner 2y ago
Stanford CS109 Probability for Computer Scientists I Normal Distribution I 2022 I Lecture 10
ML Fundamentals
Stanford CS109 Probability for Computer Scientists I Normal Distribution I 2022 I Lecture 10
Stanford Online Beginner 2y ago
Stanford CS109 Probability for Computer Scientists I Joint Distributions I 2022 I Lecture 11
ML Fundamentals
Stanford CS109 Probability for Computer Scientists I Joint Distributions I 2022 I Lecture 11
Stanford Online Beginner 2y ago
Stanford CS109 Probability for Computer Scientists I Continuous Random Variables I 2022 I Lecture 9
ML Fundamentals
Stanford CS109 Probability for Computer Scientists I Continuous Random Variables I 2022 I Lecture 9
Stanford Online Beginner 2y ago
Stanford CS109 Probability for Computer Scientists I Poisson I 2022 I Lecture 8
ML Fundamentals
Stanford CS109 Probability for Computer Scientists I Poisson I 2022 I Lecture 8
Stanford Online Beginner 2y ago
Stanford CS109 Probability for Computer Scientists I Variance Bernoulli Binomial I 2022 I Lecture 7
ML Fundamentals
Stanford CS109 Probability for Computer Scientists I Variance Bernoulli Binomial I 2022 I Lecture 7
Stanford Online Beginner 2y ago
Stanford CS109 I Random Variables and Expectation I 2022 I Lecture 6
ML Fundamentals
Stanford CS109 I Random Variables and Expectation I 2022 I Lecture 6
Stanford Online Beginner 2y ago
Stanford CS109 Probability for Computer Scientists I Independence I 2022 I Lecture 5
ML Fundamentals
Stanford CS109 Probability for Computer Scientists I Independence I 2022 I Lecture 5
Stanford Online Beginner 2y ago
Stanford CS109 I Conditional Probability and Bayes I 2022 I Lecture 4
ML Fundamentals
Stanford CS109 I Conditional Probability and Bayes I 2022 I Lecture 4
Stanford Online Beginner 2y ago
Stanford CS109 Probability for Computer Scientists I What is Probability? I 2022 I Lecture 3
ML Fundamentals
Stanford CS109 Probability for Computer Scientists I What is Probability? I 2022 I Lecture 3
Stanford Online Beginner 2y ago
Stanford CS109 Probability for Computer Scientists I Combinatorics I 2022 I Lecture 2
ML Fundamentals
Stanford CS109 Probability for Computer Scientists I Combinatorics I 2022 I Lecture 2
Stanford Online Beginner 2y ago
Stanford CS109 Probability for Computer Scientists I Counting I 2022 I Lecture 1
ML Fundamentals
Stanford CS109 Probability for Computer Scientists I Counting I 2022 I Lecture 1
Stanford Online Beginner 2y ago
Unlock new career opportunities by learning computer science,
ML Fundamentals
Unlock new career opportunities by learning computer science,
Coursera Beginner 2y ago
๐Ÿ“š Coursera Courses Opens on Coursera ยท Free to audit
1 / 3 View all โ†’
Building a Machine Learning Solution
๐Ÿ“š Coursera Course โ†—
Self-paced
Building a Machine Learning Solution
Opens on Coursera โ†—
Probabilistic Deep Learning with TensorFlow 2
๐Ÿ“š Coursera Course โ†—
Self-paced
Probabilistic Deep Learning with TensorFlow 2
Opens on Coursera โ†—
Optimize ML Models: Hyperparameter Tuning
๐Ÿ“š Coursera Course โ†—
Self-paced
Optimize ML Models: Hyperparameter Tuning
Opens on Coursera โ†—
Customising your models with TensorFlow 2
๐Ÿ“š Coursera Course โ†—
Self-paced
Customising your models with TensorFlow 2
Opens on Coursera โ†—
Advanced Deep Learning Methods for Healthcare
๐Ÿ“š Coursera Course โ†—
Self-paced
Advanced Deep Learning Methods for Healthcare
Opens on Coursera โ†—
Machine Learning Foundations: A Case Study Approach
๐Ÿ“š Coursera Course โ†—
Self-paced
Machine Learning Foundations: A Case Study Approach
Opens on Coursera โ†—