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Overview
Deep Learning based Convolutional Neural Networks (CNN) for Image recognition using Keras and Tensorflow in R Studio What you'll learn: Get a solid understanding of Convolutional Neural Networks (CNN) and Deep Learning Build an end-to-end Image recognition project in RLearn usage of Keras and Tensorflow libraries Use Artificial Neural Networks (ANN) to make predictions You're looking for a complete Convolutional Neural Network (CNN) course that teaches you everything you need to create an Image Recognition model in R, right?You've found...
Syllabus
- Introduction
- Setting Up R Studio and R crash course
- Single Cells - Perceptron and Sigmoid Neuron
- Neural Networks - Stacking cells to create network
- Important concepts: Common Interview questions
- Standard Model Parameters
- Tensorflow and Keras
- R - Dataset for classification problem
- R - Building and training the Model
- The NeuralNets Package
- R - Complex ANN Architectures using Functional API
- Saving and Restoring Models
- Hyperparameter Tuning
- CNN - Basics
- Creating CNN model in R
- Analyzing impact of Pooling layer
- Project : Creating CNN model from scratch
- Project : Data Augmentation for avoiding overfitting
- Transfer Learning : Basics
- Transfer Learning in R
- Assignment
- Congratulations & about your certificate
Instructor
Start-Tech Academy
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