Regression in Angular using TensorFlow.js

سرفصل های دوره

Learn to build regression models to datasets using machine learning in Typescript

1. Tips on coding

1. Tips on learning and reusing code code snippet

2. Interpreting the training graph

2. Discussing a simple regression model when we may have to decide the best model

1. Introduction

2. How useful are simple regression models

3. Guiding your model Absolute Error Summation vs. Mean Squared Error

4. How useful are simple regression models

5. The mechanics of teaching a neural model validation vs. training

3. Nonlinear regression and neural networks

1. Initial words

2. Back to the future imagine you could send a machine learning model backward

3. Misconception machine learning does not understand what it is doing

4. Machine learning concept features

4. Building a linear regression to predict perceived temperature

1. Preparing the environment (with the help of chatGPT)

2. Fixing initial issues, and we are good to go!

3. Running a simple model, just to get familiar with TensorFlow.js

4. Objetive ignorace mechanical judgment vs. clinical judgment

5. Uploading and visualizing our dataset

1. Uploading our dataset from Google Spreadsheet

2. Taking a look on our dataset

3. Getting to know our code for plotting

6. Creating and training our model in TensorFlow.js

1. Initial information

2. Getting familiar with our code

3. Learning to read the training curves

4. Batch size on the training curve

5. Add features to the model.html

6. Improving the sampling algorithm.html

7. Creating tensors from our dataset for training

8. Final settings for finally training our model

9. Finally our hard work pays off training the model

10. Create a test graph.html

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تولید کننده: Udemy-Training