Deep Learning For Computer Vision

Deep Learning For Computer Vision, available at $19.99, has an average rating of 3.85, with 52 lectures, based on 14 reviews, and has 90 subscribers.

You will learn about Use of Keras for image classification Pre-Processing data in order to achieve target shape Train Convolutional neural network models Understand different neural net layers Design neural networks Make predictions Serve models in a web application Learn the state of the art Computer vision techniques Computer vision projects Deep Learning This course is ideal for individuals who are Students delving in machine learning and are already comfortable with Python or Intermediate Python developers or Beginner Python developers interested in deep learning or Hobbyists interested in deep learning and computer vision It is particularly useful for Students delving in machine learning and are already comfortable with Python or Intermediate Python developers or Beginner Python developers interested in deep learning or Hobbyists interested in deep learning and computer vision.

Enroll now: Deep Learning For Computer Vision

Summary

Title: Deep Learning For Computer Vision

Price: $19.99

Average Rating: 3.85

Number of Lectures: 52

Number of Published Lectures: 52

Number of Curriculum Items: 52

Number of Published Curriculum Objects: 52

Original Price: $49.99

Quality Status: approved

Status: Live

What You Will Learn

Use of Keras for image classification
Pre-Processing data in order to achieve target shape
Train Convolutional neural network models
Understand different neural net layers
Design neural networks
Make predictions
Serve models in a web application
Learn the state of the art Computer vision techniques
Computer vision projects
Deep Learning

Who Should Attend

Students delving in machine learning and are already comfortable with Python
Intermediate Python developers
Beginner Python developers interested in deep learning
Hobbyists interested in deep learning and computer vision

Target Audiences

Students delving in machine learning and are already comfortable with Python
Intermediate Python developers
Beginner Python developers interested in deep learning
Hobbyists interested in deep learning and computer vision

The primary objective of this course is to teach you the practical hands-on skills you need to solve image classification problems – and in particular, multi-class classification. And all this, well, we shall be doing without bringing in unnecessary math logic behind it all.

In this course you will learn about the most widely used type of deep neural networks (Convolution neural network). As used by top companies all over the world like Facebook and Google.

You will learn how to use Keras in your applications to solve problems and package your models.

Build a Rest API to serve your deep learning models.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Promo video

Lecture 2: Introduction

Lecture 3: Course overview

Chapter 2: Python crash course

Lecture 1: Python refresher

Lecture 2: Python variables and lists

Lecture 3: Python dictionaries and tuples

Lecture 4: Python conditions

Chapter 3: Numpy

Lecture 1: Python Crash Course Part 1

Lecture 2: Numpy Crash Course Part 2

Lecture 3: Numpy Crash Course – Math functions

Chapter 4: Opencv Crash Course

Lecture 1: Opencv basic Introductions

Lecture 2: Grayscaling images

Lecture 3: Rescaling and resizing

Lecture 4: Image Cropping

Lecture 5: Image Rotations

Lecture 6: Blurring

Lecture 7: Edge Detection

Lecture 8: Live sketch

Lecture 9: Image face detection

Lecture 10: Live face detection

Chapter 5: Deep learning

Lecture 1: Why use keras

Lecture 2: Multiclass Classification training

Lecture 3: Multiclass Classification training part 2

Lecture 4: Multiclass Classification training part 3

Lecture 5: Multiclass Classification making prediction

Chapter 6: Emotion Classifier

Lecture 1: emotion classifier training part 1

Lecture 2: emotion classifier training part 2

Lecture 3: emotion classifier training part 3

Lecture 4: emotion classifier training part 4

Lecture 5: emotion classifier training part 5

Chapter 7: Emotion prediction

Lecture 1: emotion detection in image part 1

Lecture 2: emotion detection in image part 2

Lecture 3: emotion detection in image part 3

Lecture 4: emotion analysis

Lecture 5: emotion analysis in real time video

Chapter 8: Flask

Lecture 1: Flask Intro

Lecture 2: Flask Basics

Lecture 3: Flask web app model prediction front end building part 1

Lecture 4: Flask front end part 2 -repeat

Lecture 5: Flask front end part 3

Lecture 6: Flask back end part 1

Lecture 7: Flask back end part 2

Lecture 8: Flask back end part 3

Lecture 9: Flask back end part 4

Lecture 10: Running Web app making predictions

Chapter 9: Bonus 1

Lecture 1: Style Transfer

Chapter 10: Bonus 2 Gender classification

Lecture 1: Gender Classifier preprocessing

Lecture 2: Gender classifier training

Lecture 3: Gender classifier in web app part 1

Lecture 4: Gender classifier in web app part 2

Lecture 5: Gender classifier complete web integration

Chapter 11: Conclusion

Lecture 1: course summary

Instructors

Brightlab Tech
IT Traininng

Rating Distribution

1 stars: 1 votes
2 stars: 1 votes
3 stars: 2 votes
4 stars: 2 votes
5 stars: 8 votes

Frequently Asked Questions

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