Data Science and Machine Learning Series: Advanced Convolutional Neural Networks (CNNs) and Transfer Learning

January 30, 2020 Courses
Data Science and Machine Learning Series: Advanced Convolutional Neural Networks (CNNs) and Transfer Learning

English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 1h 49m | 289 MB

Follow along with machine learning expert Advait Jayant through a combination of lecture and hands-on and master the practical aspects of Convolutional Neural Networks (CNNs) and transfer learning.

The following seven topics will be covered in this Data Science and Machine Learning course:

  • Building a Small CNN to Classify Handwritten Digits. Build a small Convolutional Neural Network (CNN) to classify handwritten digits in this first topic in the Data Science and Machine Learning Series. Follow along with Advait and work with the MNIST Handwritten Digits Dataset.
  • Training the CNN Model in Keras. Train the Convolutional Neural Network (CNN) Model in Keras in this second topic in the Data Science and Machine Learning Series.
  • The Practical Aspects of Image Data Augmentation. Become proficient with the practical aspects of image data augmentation in this third topic in the Data Science and Machine Learning Series.
  • Introducing Transfer Learning. Master transfer learning in this fourth topic in the Data Science and Machine Learning Series.
  • Implementing Transfer Learning in Keras. Implement transfer learning in Keras in this fifth topic in the Data Science and Machine Learning Series. Follow along with Advait and practice using different models for prediction and feature extraction including Xception, VGG16, VGG19, ResNet, ResNetV2, MobileNet, DenseNet, and NasNet.
  • Feature Extraction and Fine Tuning. Use both feature extraction and fine tuning and know when to use each approach in this sixth topic in the Data Science and Machine Learning Series. Follow along with Advait and apply feature extracting and fine tuning in four different scenarios.
  • Implementing Feature Extraction and Transfer Learning using ResNet-50 Base. Implement feature extraction and transfer learning using ResNet-50 Base in this seventh topic in the Data Science and Machine Learning Series.
Table of Contents

1 Building a Small CNN to Classify Handwritten Digits
2 Training the CNN Model in Keras
3 The Practical Aspects of Image Data Augmentation
4 Introducing Transfer Learning
5 Implementing Transfer Learning in Keras
6 Feature Extraction and Fine Tuning
7 Implementing Feature Extraction and Transfer Learning using ResNet-50 Base

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