Deep Learning

Dig: Apply Deep Learning models to gain insights from the Data

Introduction

1. Good sources, courses to start with Deep Learning (comming soon)

2. Introduction to Neural Network, Perceptrons, Deep Learning, When to use Deep Learning?

3. Important points to remember in during developing a deep learning project.

4. Revisit to Vectorization, Broadcasting and Assertion statement

5. Dropout Regularization (Coming soon)

Useful Packages

1. Steps to Install Tensorflow, Keras, OpenCV

Google APIs for image and text analysis

Keras and Tenserflow Examples

1. Keras basics: parameters

2. Simple linear regression model example using keras: explanation and code

3. OCR to read single handwritten number from an image

OpenCV

1. Abour OpenCV? Image processing? Exploring some of the Image processing Modules in the OpenCV. (Coming soon)

2. Video processing example using OpenCV (Coming soon)

3. In live video detect face/object using OpenCV (Coming soon)

4. End-to-end image tilt angle detection and correction using Canny edges and hough lines detection techniques.

Optical Character recognition-LSTM (RNN)

1. Introduction to Google Tesseract. Installation steps

2. OCR example using Tesseract 3.0 and 4.0. (For FAQ refer this Link)

3. Techniques to Improving accuracy of the output of Tesseract

4. OCR using Google Vision API (coming soon)

AI cheat sheet for RNN, LSTM and GRU

Convolutional Neural Network-Image Processing

1. Introduction to CNN? Where we can use the CNN?

Residual neural Network (ResNet)

1. Whats is vanishing gradient problem? What is ResNet how it solves this problem using skip connection?

2. Implementation of ResNet using Keras. (coming soon)

3. What is the problems with ResNet?

4. Detection of Age and Gender In live video using Wide Residual Networks in Keras. (coming soon)

AI cheat sheet for Deep Residual Network (DRN)

Auto-encoder

1. End to End Auto encoder for anomaly detection (coming soon)

2. Problem with Auto encoders? what is Adversarial Auto Encoder?

3. End to End Adversarial auto encoder for anomaly detection (coming soon)

AI cheat sheet for AE, VAE, DAE and SAE

Medical Images (.dcm files)

1. Read x-ray in .dcm format and explore pydicom features (Coming soon)

2. Simple U-net model for segmentation
   

3. U-Net: Convolutional Networks for Biomedical Image Segmentation Paper by Olaf Ronneberger, Philipp Fischer, and Thomas Brox

4. End to end detection and segmentation of the nuclei in divergent images using simple U-net model in Keras Python

5. Auto-encoder and Adversarial Auto-encoder for anomaly detection (Coming soon)

Interesting Deep Learning techniques

1. What is Generative adversarial network (GAN)? What is Generative and Indiscriminate networks? (coming soon)

2. You only look once (YOLO) algorithm for faster object detection. (coming soon)

Some useful articles on other websites:

1. Create a new notebook instance/AI Platform Notebooks (JupyterLab) instance (Deep Learning virtual machine instance) on Google Cloud. Link