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Neural Networks and Random Forests 

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Neural Networks and Random Forests
 at 
Coursera 
Overview

Duration

10 hours

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Total fee

Free

Mode of learning

Online

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Credential

Certificate

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
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Neural Networks and Random Forests
 at 
Coursera 
Course details

More about this course
  • 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

Neural Networks and Random Forests
 at 
Coursera 
Admission Process

    Important Dates

    May 25, 2024
    Course Commencement Date

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    Neural Networks and Random Forests
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