Machine Learning 1: Lesson 8

preview_player
Показать описание
Today we start the second half of the course - we're moving from decision tree based approaches like random forests, to gradient descent based approaches like deep learning.

Our first step in this journey will be to use Pytorch to help us implement logistic regression from scratch. We'll be building a model for the classic MNIST dataset of hand-written digits.
  1. Jeremy Howard
  2. fastai
  3. machine learning
Рекомендации по теме
Machine Learning 1: 1:33:46

Machine Learning 1: Lesson 8

Neural Network Architecture 0:33:38

Neural Network Architecture in Machine Learning | Lesson 8

#16 Machine Learning 0:12:14

#16 Machine Learning Engineering for Production (MLOps) Specialization [Course 1, Week 2, Lesson 8]

#8 Machine Learning 0:09:33

#8 Machine Learning Engineering for Production (MLOps) Specialization [Course 1, Week 1, Lesson 8]

Random Forests - 0:06:15

Random Forests - Machine Learning in Python Tutorial (Lesson 8)

Lesson 8 - 1:36:55

Lesson 8 - Practical Deep Learning for Coders 2022

Machine Learning | 0:07:52

Machine Learning | What Is Machine Learning? | Introduction To Machine Learning | 2024 | Simplilearn

Lesson 8 (2019) 2:06:41

Lesson 8 (2019) - Deep Learning from the Foundations

EfficientML.ai Lecture 4 1:09:20

EfficientML.ai Lecture 4 - Pruning and Sparsity Part II (MIT 6.5940, Fall 2024, Zoom recording)

Lesson 8 - 1:56:58

Lesson 8 - Deep Learning for Coders (2020)

Lesson 8: Cutting 1:47:09

Lesson 8: Cutting Edge Deep Learning for Coders

Finding the Maximum 0:10:03

Finding the Maximum and Minimum of a Function for Machine Learning || Lesson 8 || Machine Learning

LESSON 8: MASTERING 0:14:19

LESSON 8: MASTERING MACHINE LEARNING ALGORITHM: Analyzing Density Function

Deep Learning | 0:05:52

Deep Learning | What is Deep Learning? | Deep Learning Tutorial For Beginners | 2023 | Simplilearn

Machine Learning with 0:13:18

Machine Learning with python Course - Lecture 7 - Logistic Regression with one variable - M.Gamal

Machine Learning 1: 1:41:42

Machine Learning 1: Lesson 12

Supervised vs Unsupervised 0:06:27

Supervised vs Unsupervised vs Reinforcement Learning | Machine Learning Tutorial | Simplilearn

Machine Learning 1: 1:36:07

Machine Learning 1: Lesson 11

Machine Learning Tutorial 0:06:34

Machine Learning Tutorial Python - 7: Training and Testing Data

Machine Learning with 18:00:35

Machine Learning with Python and Scikit-Learn – Full Course

Lesson 8 - 0:07:48

Lesson 8 - Basic Data Analysis in R Linear Regression

Lung inflation in 0:00:16

Lung inflation in Science Lesson #science #teacher #biology

Lesson 8: Part 0:23:52

Lesson 8: Part 1 - Opening Lecture

#32 Machine Learning 0:12:28

#32 Machine Learning Engineering for Production (MLOps) Specialization [Course 1, Week 3, Lesson 8]

Комментарии
Автор

at 1:23:16 When you defined get_weights, you only had one parameter, but when you used it in the LogReg, you passed in 2 parameters. I dont really understand that

ihgnmah
Автор

What does Jeremy mean what he says, "You can only do around log2(n) decisions, so if there's a time series it needs to fit to that takes four steps, then suddenly there's not many decisions for it left to make" (1:33) How does he reach this conclusion?

ho
Автор

MNIST link dead :( deeplearning.net unavailable....

ashpats
Автор

18:19 that is not normalization, it's standardization. Normalization is scaling the data to the minimum and maximum.

bijan
Автор

What do I need to know to build a deep learning framework? please tell me the courses and books. please answer me

aidenstill