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Byte Size ML
เข้าร่วมเมื่อ 28 มี.ค. 2022
Byte Sized Machine Learning Content - Also, lectures from courses on Machine Learning!
Lecture 9 | LLM 2025 Lectures
Lecture delivered at the University of Washington, Seattle as part of the LLM course in the Professional Masters program at ECE, UW
Webpage and Lecture Materials: bytesizeml.github.io/llm2025/
0:00 Introduction & House Keeping
8:22 Todays Lecture overview
13:22 Recap - Transformers Overview
20:06 In-class Exercise I
24:11 In-class Exercise II
26:27 Prompt Engineering for NLP applications
Webpage and Lecture Materials: bytesizeml.github.io/llm2025/
0:00 Introduction & House Keeping
8:22 Todays Lecture overview
13:22 Recap - Transformers Overview
20:06 In-class Exercise I
24:11 In-class Exercise II
26:27 Prompt Engineering for NLP applications
มุมมอง: 43
วีดีโอ
Lecture 8 | LLM 2025 Lectures
มุมมอง 1089 ชั่วโมงที่ผ่านมา
Lecture delivered at the University of Washington, Seattle as part of the LLM course in the Professional Masters program at ECE, UW Webpage and Lecture Materials: bytesizeml.github.io/llm2025/ 0:00 Introduction 1:59 Transformer Types 6:10 Multi-Head Attention overview 12:56 Single-Head Attention 33:59 Multi-Head Attention walkthrough 39:21 Self-Attention Math walkthrough 57:54 Feed-Forward Math...
Lecture 7 | LLM 2025 Lectures
มุมมอง 199วันที่ผ่านมา
Lecture delivered at the University of Washington, Seattle as part of the LLM course in the Professional Masters program at ECE, UW Webpage and Lecture Materials: bytesizeml.github.io/llm2025/ 0:00 Language Model Recap 9:53 Product2Vec | eCommerce Applications 16:46 View Similarity and Purchase Similarity 28:00 Improving Sentence Embeddings 30:27 Transformers Architecture and BERT 43:05 Vocab, ...
Lecture 6 | LLM 2025 Lectures
มุมมอง 509วันที่ผ่านมา
Lecture delivered at the University of Washington, Seattle as part of the LLM course in the Professional Masters program at ECE, UW Webpage and Lecture Materials: bytesizeml.github.io/llm2025/ 0:00 Recap on Recommender Systems 9:01 Vector Search and Semantic Search 21:16 DeepSeek Disruption 35:11 In-Class Exercise on Cosine Similarity 42:31 Word2Vec Model (muted)
Lecture 5 | LLM 2025 Lectures
มุมมอง 17914 วันที่ผ่านมา
Lecture delivered at the University of Washington, Seattle as part of the LLM course in the Professional Masters program at ECE, UW Webpage: bytesizeml.github.io/llm2025/ 0:00 Netflix Recommendations 9:10 Collaborative Filtering 18:35 Matrix Factorization and SVD 31:50 Cold-Start Problem 35:02 Content Based Filtering 43:02 Embeddings and Cosine Similarity 1:01:00 Word Embeddings and Semantic Se...
Lecture 4 | LLM 2025 Lectures
มุมมอง 51014 วันที่ผ่านมา
Lecture delivered at the University of Washington, Seattle as part of the LLM course in the Professional Masters program at ECE, UW Webpage: bytesizeml.github.io/llm2025/ 0:00 Outline for Lecture 6:54 Forward Propagation | XOR 24:14 Computer Vision and Deep Learning 33:40 In-Class Exercise 39:09 Training a DNN 45:52 Stochastic Gradient Descent (SGD)
Lecture 3 | LLM 2025 Lectures
มุมมอง 18121 วันที่ผ่านมา
Lecture delivered at the University of Washington, Seattle as part of the LLM course in the Professional Masters program at ECE, UW Webpage: bytesizeml.github.io/llm2025/ 0:00 Outline for Lecture 11:21 Recap on Perceptrons, Logistic Regression 21:33 Learning XOR 24:01 Why does Linear Activation not work? 31:18 Step Function as Activation 34:26 Recap on 2 layer NN 36:46 In-Class Exercise 1 39:34...
Lecture 2 | LLM 2025 Lectures
มุมมอง 470หลายเดือนก่อน
Lecture delivered at the University of Washington, Seattle as part of the LLM course in the Professional Masters program at ECE, UW Webpage: bytesizeml.github.io/llm2025/ 0:00 Introduction 3:01 Engines vs API 8:31 What is a Language Model? 22:44 LLMs and their history 51:22 NLP use cases for ChatGPT 59:30 Deep Learning Fundamentals 1:02:08 Deep Learning Applications 1:09:35 Brief History of Dee...
Lecture 1 | LLM 2025 Lectures
มุมมอง 804หลายเดือนก่อน
Lecture delivered at the University of Washington, Seattle as part of the LLM course in the Professional Masters program at ECE, UW Webpage: bytesizeml.github.io/llm2025/ 0:00 Introduction 5:29 ChatGPT Motivation 7:26 ChatGPT 4o Live Examples 35:51 How to understand ChatGPT? 37:57 Course Outline
Best Practices of ChatGPT for NLP Applications
มุมมอง 1579 หลายเดือนก่อน
We look at how ChatGPT and other LLMs get used in the industry these days with a focus on keyword extraction, summarization, LLM-based data annotation and LLM-based data augmentation. 2:30 Introduction 7:00 Engine Behind ChatGPT 10:20 History behind LLMs 19:54 ChatGPT use cases for NLP 32:44 Hybrid Models 34:27 Benchmarking LLMs 37:13 Benchmarking LLMs in business
Business use-cases for LLMs | LLM 2024 Last Lecture
มุมมอง 8910 หลายเดือนก่อน
Lecture on Business Use for LLMs. Lecture Webpage: bytesizeml.github.io/llm2024
TensorFlow Playground Demo (Beginner Friendly)
มุมมอง 307ปีที่แล้ว
Instructive video that includes concepts on overfitting, linear/non-linear models, activation functions and feed forward nets 0:00 ML Concepts Refresher 7:52 TensorFlow Playground Walk-through
Transformer Architectures Breakdown | Combinations of Encoders and Decoders
มุมมอง 164ปีที่แล้ว
In this video - We breakdown Transformer Models into 4 different combinations that get used in practice - Encoder only, Decoder only, Encoder-Decoder and Encoder-Encoder Architectures.
Lecture 5 (recorded) | Features for Text Data | Bow and Tf-Idf
มุมมอง 1112 ปีที่แล้ว
Course Website: bytesizeml.github.io/ml2023 This is the 5th "recorded" lecture in the lecture series on "Advanced Introduction to Machine Learning". In this lecture we look at features for text data. 0:00 Logistics 0:42 Features for Text Data 3:57 Bag of Words Example 11:44 Pre-processing Text Data 14:46 N-grams 18:16 In-Class Exercise #1 21:36 TF-IDF 29:41 In-Class Exercise #2 32:45 Scalable R...
Lecture 5 | Binary Classification and Classification Metrics
มุมมอง 1442 ปีที่แล้ว
Course Website: bytesizeml.github.io/ml2023 This is the 5th lecture in the lecture series on "Advanced Introduction to Machine Learning". In this lecture we look at binary classification, models for classification and its evaluation metrics. 0:00 Logistics 4:32 Today's Class 5:02 Classification in Machine Learning 7:40 Classification vs Regression 15:05 Types of Classification 18:07 Examples of...
Lecture 1 | Advanced Intro to ML | Winter 2023
มุมมอง 8732 ปีที่แล้ว
Lecture 1 | Advanced Intro to ML | Winter 2023
Lecture 2 | Advanced Intro to Machine Learning | Winter 2023
มุมมอง 1532 ปีที่แล้ว
Lecture 2 | Advanced Intro to Machine Learning | Winter 2023
Lecture 3 | Advanced Intro to Machine Learning | Linear Regression
มุมมอง 1192 ปีที่แล้ว
Lecture 3 | Advanced Intro to Machine Learning | Linear Regression
Lecture 4 | Overfitting and SGD | Advanced Intro to Machine Learning
มุมมอง 902 ปีที่แล้ว
Lecture 4 | Overfitting and SGD | Advanced Intro to Machine Learning
Computer Vision | CNN Architectures | Lecture 11
มุมมอง 792 ปีที่แล้ว
Computer Vision | CNN Architectures | Lecture 11
Computer Vision | Residual Nets | Lecture 12
มุมมอง 392 ปีที่แล้ว
Computer Vision | Residual Nets | Lecture 12
Computer Vision | CNN Introduction | Lecture 10
มุมมอง 1822 ปีที่แล้ว
Computer Vision | CNN Introduction | Lecture 10
Computer Vision | Transfer Learning and Pre-Trained Models | Lecture 13
มุมมอง 2012 ปีที่แล้ว
Computer Vision | Transfer Learning and Pre-Trained Models | Lecture 13
Computer Vision | Lecture 7 | Image Classification Metrics and Overfitting
มุมมอง 1582 ปีที่แล้ว
Computer Vision | Lecture 7 | Image Classification Metrics and Overfitting
Lecture 6 - Binary Classification | Computer Vision
มุมมอง 632 ปีที่แล้ว
Lecture 6 - Binary Classification | Computer Vision
Computer Vision | Lecture 5 | Computational Complexity and Total Variation
มุมมอง 1722 ปีที่แล้ว
Computer Vision | Lecture 5 | Computational Complexity and Total Variation
Computer Vision | Lecture 4 | kMeans, kMeans++ and tSNE
มุมมอง 552 ปีที่แล้ว
Computer Vision | Lecture 4 | kMeans, kMeans and tSNE
Lecture 2: SVD and Image Compression | Computer Vision Course | Udub, Seattle
มุมมอง 1092 ปีที่แล้ว
Lecture 2: SVD and Image Compression | Computer Vision Course | Udub, Seattle
Lecture 3: SVD and Convolutions | Computer Vision Course | Udub, Seattle
มุมมอง 1632 ปีที่แล้ว
Lecture 3: SVD and Convolutions | Computer Vision Course | Udub, Seattle
Computer Vision | Lecture 1 | Udub, Seattle 2022
มุมมอง 3452 ปีที่แล้ว
Computer Vision | Lecture 1 | Udub, Seattle 2022
awesome!!
Thanks ❤❤
Thanks for sharing.
Any course for coding especially for beginners
yes there is a course coming up for interviewing in April
can youtube audiance can have the assesment and coding assignment link, So that we can also practice.?
Going to be tricky to do that. Best to enroll in a class for maximal learning.
As you are uploading it after recording is there any way we can attend the live course and lecture so that we can also put on question> Thanks
are you going to complete the whole course
Yess!
What is the pre requisite for these lectures
basic understanding of machine learning is needed - other topics you can catch up as you watch the lectures
Great job! You explained it very well
Amazing first lecture to CV. I didn't take this course due to my lack of knowledge in Machine Learning, thus Ill be seeing you in Advanced Introduction to Machine Learning to prepare me for a Data Scientist and or Machine Learning Engineer Role.
see you there!
09:00 - Linear Model with an example of an Non Linear Feature 12:00 - a new Feature Engineered - independent variable - h(x) 15:00 - SIFT features 16:00 - Deep learning algorithms - learning to feature engineer . 20:30 - Given data is Linear Separable , Logistic Regression ( Classification ) is a good choice . 25:30 - Logistic Regression --> is a ONE CELL Neural Network - its just ONE NEURON 26:30 - Loss Function --> Optimizing for w(hat) - by picking the RIGHT w(hat) , we ensure that the Y(hat)i is close to most Yi 28:40 - ENTROPY - both the classes - 0 and 1 have equal probability - 0.5 ( 50%) and thus its the Highest Uncertaintiy or Hihghest Entropy
Thanks for the additional time stamps