Neural Networks and Random Forests
- Offered byCoursera
- Public/Government Institute
Neural Networks and Random Forests at Coursera Overview
Duration | 10 hours |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
- Overview
- Highlights
- Course Details
- Curriculum
Neural Networks and Random Forests at Coursera Highlights
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Course 3 of 4 in the AI for Scientific Research Specialization
- Intermediate Level I't is reccomended that you complete the first two courses in the specialization before starting this one.
- Approx. 10 hours to complete
- English Subtitles: English
Neural Networks and Random Forests at Coursera Course details
- In this course, we will build on our knowledge of basic models and explore advanced AI techniques. We will start with a deep dive into neural networks, building our knowledge from the ground up by examining the structure and properties. Then we will code some simple neural network models and learn to avoid overfitting, regularization, and other hyper-parameter tricks. After a project predicting likelihood of heart disease given health characteristics, we will move to random forests. We will describe the differences between the two techniques and explore their differing origins in detail. Finally, we will complete a project predicting similarity between health patients using random forests.
Neural Networks and Random Forests at Coursera Curriculum
Introduction to Neural Networks
Course Intro
Module Intro
Neural Network Visualized
Loss Functions
Activation Functions
Neural Network Playground
Backpropagation
Common Activation Functions
Feed Forward and Backpropagation
Neural Network Basics
Module Intro
Introduction to TensorFlow and Keras
Deep Dive into Keras
Implementing a ML Model with Tensorflow and Keras
Bias-Variance Tradeoff
Configuring the Learning Rate
Multi-Layer Networks
Scientific Article: Neural Networks in Bioinformatics
Advanced Neural Networks
Exploring Random Forests
Module Intro
Exploring Trees
Scitkit-learn docs: Random Forest Classifier
Scikit-learn Docs: Random Forest Regressor
Final Project: Comparing Models to Predict Sepal Width
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