Predicting Diabetes with Logistic Regression in TensorFlow.js - Deep Learning for JavaScript Hackers
Offered By: Venelin Valkov via YouTube
Course Description
Overview
Learn to build a Logistic Regression model in TensorFlow.js using the high-level layers API to predict diabetes in patients. Explore data visualization techniques, dataset creation, and model training and evaluation. Dive into key concepts including logistic regression, TensorFlow.js model types, cross-entropy loss function, and confusion matrices. Follow along as the tutorial progresses from basic model implementation to training more complex models with additional features. Gain practical insights into deep learning for JavaScript through hands-on coding and comprehensive explanations of each step in the process.
Syllabus
- What is Logistic Regression?
- Types of models in TensorFlow.js
- Build a Logistic Regression model in TensorFlow.js
- Cross-entropy loss function
- Training evaluation
- Training a model with more features
- Display the confusion matrix
- Train a more complex model
Taught by
Venelin Valkov
Related Courses
Neural Networks for Machine LearningUniversity of Toronto via Coursera 機器學習技法 (Machine Learning Techniques)
National Taiwan University via Coursera Machine Learning Capstone: An Intelligent Application with Deep Learning
University of Washington via Coursera Прикладные задачи анализа данных
Moscow Institute of Physics and Technology via Coursera Leading Ambitious Teaching and Learning
Microsoft via edX