Practical Transfer Learning ( Deep Learning )in Python

Practical Transfer Learning ( Deep Learning )in Python, available at $39.99, has an average rating of 4.1, with 54 lectures, based on 105 reviews, and has 11801 subscribers.

You will learn about Transfer Learning for Image Classification Google Teachable Machine Transfer Learning in Python Deep Learning on Steroid This course is ideal for individuals who are Deep Learning Enthusiastic or Anyone who want to jump start Machine Learning It is particularly useful for Deep Learning Enthusiastic or Anyone who want to jump start Machine Learning.

Enroll now: Practical Transfer Learning ( Deep Learning )in Python

Summary

Title: Practical Transfer Learning ( Deep Learning )in Python

Price: $39.99

Average Rating: 4.1

Number of Lectures: 54

Number of Published Lectures: 53

Number of Curriculum Items: 54

Number of Published Curriculum Objects: 53

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Transfer Learning for Image Classification

Google Teachable Machine

Transfer Learning in Python

Deep Learning on Steroid

Who Should Attend

Deep Learning Enthusiastic

Anyone who want to jump start Machine Learning

Target Audiences

Deep Learning Enthusiastic

Anyone who want to jump start Machine Learning

Don’t be Hero . as It is well said..

Let;s Enroll and utilize works of Hero for our problems.

Everyone can not do research like Yann Lecun or Andrew Ng. They are focused on improving machine learning algorithms for better world.

But as an individual and for industry, we are more concern with specific application and its accuracy.

Transfer Learning is the solution for many existing problems. Transfer learning uses existing knowledge of previously learned model to new frontier.

I will demonstrate code to do Transfer Learning in Image Classification.

Knowledge gain to recognize cycle and bike can be used to recognize car.

There are various ways we can achieve transfer learning. I will discuss Pre trained model, Fine tunning and feature extraction techniques.

Once again. Let’s not be Hero . and enroll in this course.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction and Course Outline

Lecture 2: Do you want to be poet?

Lecture 3: Becoming Poet Part 1

Lecture 4: Becoming Poet Part 2

Lecture 5: Becoming Poet Part 3

Lecture 6: Three main motivation for Transfer Learning

Lecture 7: Success of Transfer Learning – Andrew Ng

Lecture 8: Transfer Learning vs Traditional ML and Deep Learning

Lecture 9: Transfer Learning vs Traditional ML and Deep Learning 2

Chapter 2: Understanding Transfer Learning

Lecture 1: Basic Understanding of Transfer Learning

Lecture 2: Technical Terms of Transfer Learning

Lecture 3: What , How and When to do Transfer Learning

Lecture 4: Negative Transfer Learning

Lecture 5: Inductive Bias

Lecture 6: Transfer Learning in Deep Learning

Lecture 7: Types of Transfer Learning in Deep Learning

Lecture 8: Top-1 and Top-5 Accuracy

Chapter 3: Google Teachable Machine – Unlimited edge for Transfer Learning

Lecture 1: Introduction to Teachable Machine

Lecture 2: Mask Face Classification

Lecture 3: Indian Rupee Classification

Lecture 4: Audio Classification – Man in Black

Lecture 5: Audio Classification – Bell and Clap

Lecture 6: Pose Classification – Bad Posture

Lecture 7: Pose Classification – Yoga pose

Lecture 8: Yoga Pose Testing

Lecture 9: Tensorflow.js Model Deployment with p5

Lecture 10: More Internal Deployment

Lecture 11: Labels and Confidence Detail

Lecture 12: Android Deployment

Chapter 4: Worth Reading Articles

Lecture 1: Articles

Chapter 5: Transfer Learning in Python

Lecture 1: Downloaded Model Location

Lecture 2: Direct Use of Model

Lecture 3: Dataset Preparation for Custom Model

Lecture 4: Making of Custom Model – Last Layer change

Lecture 5: Fitting of Custom Model – 4 Class Model

Chapter 6: Monkey Species Classification

Lecture 1: Model Downloading

Lecture 2: Existing Models Checking

Lecture 3: Data Loading -1

Lecture 4: Data Loading One Hot Encoding

Lecture 5: Resnet Custom Model

Lecture 6: Fitting Custom Resnet Model

Lecture 7: Basic CNN Model on Monkey Dataset

Lecture 8: Fitting Basic Model

Lecture 9: Thank you – For the Course

Chapter 7: (Optional ) 4 Classes Model (Cat , dog, horse, human)

Lecture 1: Checking against pre-trained model

Lecture 2: Dataset Preparation for Custom Model

Lecture 3: Custom Model

Lecture 4: Fitting the Model

Chapter 8: (Optional)Full Demo – DOG CAT Classifier

Lecture 1: Data Preparation-1

Lecture 2: Image to Numpy Array

Lecture 3: Label Encoding

Lecture 4: Basic CNN Model-1

Lecture 5: CNN Model-2 with Drop out and More layer

Instructors

Mosin hasan
Engineer – Computer Science

Rating Distribution

1 stars: 5 votes

2 stars: 8 votes

3 stars: 21 votes

4 stars: 32 votes

5 stars: 39 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!