Uploads from StatQuest with Josh Starmer

Watch and track your favorite playlist.

Curated by: StatQuest with Josh Starmer (303 videos)

---

Tracks in this Playlist

• Support Vector Machines (SVM): Concepts and Code
• Triple BAM! Live with Jon Krohn, Josh Starmer, and Luis Serrano!
• Naive Bayes: Concepts and Code
• The GELU, SiLU and SwiGLU activation functions, clearly explained!!!
• Another three (3) more lessons from my Pop!
• TRIPLE BAM!!! With Josh, Luis and special guest Brandon Rohrer
• The Simplex Algorithm, Mathematical Details!!!
• Optimization with Linear Programming (and the Simplex Algorithm), Main Ideas!!!
• StatQuest: Random Forests Part 2: Missing data and clustering
• False Discovery Rates, FDR, clearly explained
• The Essence of Linear Regression!!!
• How AI works in Super Simple Terms!!!
• StatQuest: Career Advice from Tech Industry Leaders
• Reinforcement Learning with Human Feedback (RLHF), Clearly Explained!!!
• Reinforcement Learning with Neural Networks: Mathematical Details
• Reinforcement Learning with Neural Networks: Essential Concepts
• Reinforcement Learning: Essential Concepts
• StatQuest on DeepLearning.AI!!! Check out my short course on attention!
• StatQuest with Josh Starmer is live!
• Encoder-Only Transformers (like BERT) for RAG, Clearly Explained!!!
• Luis Serrano + Josh Starmer Q&A Livestream!!!
• Human Stories in AI: Nana Janashia@TechWorld With Nana
• A few more lessons from my Pop!
• Human Stories in AI: Abbas Merchant@Matics Analytics
• Luis Serrano + Jay Alammar + Josh Starmer Q&A Livestream!!!
• Coding a ChatGPT Like Transformer From Scratch in PyTorch
• Human Stories in AI: Amy Finnegan
• Human Stories in AI: Xavier Moyá
• Human Stories in AI: Tommy Tang
• Luis Serrano + Josh Starmer Q&A Livestream!!!
• Human Stories in AI: Simon Stochholm
• Log_e Song - Official Lyric Video
• Human Stories in AI: Brian Risk@devra.ai
• The matrix math behind transformer neural networks, one step at a time!!!
• Human Stories in AI: Fabio Urbina
• Human Stories in AI: Khushi Jain
• Human Stories in AI: Achal Dixit
• Human Stories in AI: Rick Marks
• Essential Matrix Algebra for Neural Networks, Clearly Explained!!!
• Word Embedding in PyTorch + Lightning
• The Golden Play Button, Clearly Explained!!!’
• Another 3 lessons from my Pop!!!
• Decoder-Only Transformers, ChatGPTs specific Transformer, Clearly Explained!!!
• Transformer Neural Networks, ChatGPT's foundation, Clearly Explained!!!
• What is a Logit?
• Logistic vs Logit Functions
• Attention for Neural Networks, Clearly Explained!!!
• Likelihood vs Probability
• p-values
• Sequence-to-Sequence (seq2seq) Encoder-Decoder Neural Networks, Clearly Explained!!!
• Matrix Multiplication
• Matrix Notation
• The Ukulele: Clearly Explained!!!
• PCA Eigenvalues
• PCA Eigenvectors
• Normalized Data
• Standardized Data
• Type 2 Errors
• Type 1 Errors
• Word Embedding and Word2Vec, Clearly Explained!!!
• The AI Buzz, Episode #5: A new wave of AI-based products and the resurgence of personal applications
• CatBoost Part 2: Building and Using Trees
• CatBoost Part 1: Ordered Target Encoding
• The AI Buzz, Episode #4: ChatGPT + Bing and How to start an AI company in 3 easy steps.
• One-Hot, Label, Target and K-Fold Target Encoding, Clearly Explained!!!
• The AI Buzz, Episode #3: Constitutional AI, Emergent Abilities and Foundation Models
• Mutual Information, Clearly Explained!!!
• Cosine Similarity, Clearly Explained!!!
• Long Short-Term Memory with PyTorch + Lightning
• The AI Buzz, Episode #2: Big data, Reinforcement Learning and Aligning Models
• The AI Buzz, Episode #1: ChatGPT, Transformers and Attention
• Design Matrix Examples in R, Clearly Explained!!!
• Design Matrices For Linear Models, Clearly Explained!!!
• Using Linear Models for t tests and ANOVA, Clearly Explained!!!
• Multiple Regression in R, Step by Step!!!
• Multiple Regression, Clearly Explained!!!
• Linear Regression in R, Step by Step
• Linear Regression, Clearly Explained!!!
• R-squared, Clearly Explained!!!
• Long Short-Term Memory (LSTM), Clearly Explained
• The Cosine Similarity for NLP and CatBoost
• Happy Halloween (Neural Networks Are Not Scary)
• Handmade Pasta, Clearly Explained!!!
• Live Stream - More details about Target Encoding/AMA/Silly Songs
• Live Stream - Target Encoding/AMA/Silly Songs!!!
• Introduction to Coding Neural Networks with PyTorch and Lightning
• Three more lessons from my Pop!!!
• Recurrent Neural Networks (RNNs), Clearly Explained!!!
• The StatQuest Illustrated Guide To Machine Learning, Theme Song!!!
• The StatQuest Introduction to PyTorch
• Troll 2, Clearly Explained!!!
• The Binomial Distribution in 30 Seconds!!!
• UMAP: Mathematical Details (clearly explained!!!)
• UMAP Dimension Reduction, Main Ideas!!!
• Tensors for Neural Networks, Clearly Explained!!!
• The Sensitivity, Specificity, Precision, Recall Sing-a-Long!!!
• The Exponential Distribution
• The mean, the median, and the mode.
• Clustering with DBSCAN, Clearly Explained!!!
• Frank Starmer Clearly Explained (How my pop influenced StatQuest!!!)