Deep Learning Bootcamp with 5 Capstone Projects

Learn about Deep Learning - ANN, CNN, RNN, LSTMs along with Real Time Capstone Projects

4.20 (214 reviews)
Udemy
platform
English
language
Data Science
category
19,476
students
6.5 hours
content
Mar 2022
last update
$79.99
regular price

What you will learn

Learn about Artificial Neural Networks.

Learn about the different Layers present in a Neural Networks.

Learn about different Activation Functions used in a Neural Network.

Learn to Hyper tune the Neural Networks to Improve Performance.

Implement Artificial Neural Networks to solve real world Problems.

Learn about Convolutional Neural Networks.

Learn about different Layers of a Convolutional Neural Networks.

Learn about Dropout and Callbacks in Neural Networks.

Learn about the Recurrent Neural Networks.

Implement the LSTMs to solve Sequential Problems.

Use Real World Examples

Description

Are you ready to master Deep Learning skills?

Deep Learning is a technology using which we can solve highly computational problems such as Image Processing, Image Classification, Image Segmentation, Image tagging, sound classification, video analysis, etc.

Deep Learning is becoming a buzzword these days, and If you want to learn Deep Learning then It is very important for you that you should have a proper plan regarding that.

Before Learning Deep Learning you must have learned Machine Learning and must possess good knowledge of the Python programming language.


If you want to build super-powerful applications in Deep Learning. Then, you are at the right place.

This course will provide you with in-depth knowledge on a very hot topic i.e., Deep Learning.

The purpose of this course is to provide you with knowledge of key aspects of Deep Learning without any intimidating mathematics and in a practical, easy, and fun way. The course provides students with practical hands-on experience using real-world datasets.


This course will cover the following topics:-

1. Deep Learning (DL).

2. Artificial Neural Network (ANN).

3. Convolutional Neural Network (CNN).

4. Recurrent Neural Network. (RCN)

5. Learn to Implement the LSTMs.


This course will take you through the basics to an advanced level in all the mentioned four topics.

After taking this course, you will be confident enough to work independently on any projects on these topics.

There are lots and lots of exercises for you to practice In this Deep Learning Course and also a  5 Bonus Deep Learning Project "Stock Market Prediction", "Fruits Identification System", "Face Expression Recognizer", "Detecting Pneumonia from Chest X-rays", and "Optimizing Crop Production".


In this Optimizing Crop Production, you will learn about Precision Farming using Data Science Technologies such as Clustering Analysis and Classification Analysis. You will be able to Recommend the best Crops to Farmers to Increase their Productivity.

In this Detecting Pneumonia from X-rays project, you will learn how to solve Image Classification Tasks using Deep Neural Networks such as ResNet which is a High-Level CNN Architectures.

In this Stock Market Prediction project, you will learn to analyze, and the Stock Market Prices using Time Series Forecasting, Advanced Deep Learning Models, and different Statistical features.

In this Fruits Recognition project, you will learn how to solve a complicated Image Classification Task with Multiple Classes using various Deep Learning Architectures and Compare the Result.

In this Face Expression Recognizer project, you will learn to use Computer Vision Techniques to detect Human Emotions such as Angry, Sad, Happy, Disgust, Fear, etc. to build a Facial Emotion Detector.

Instructor Support - Quick Instructor Support for any queries.

I'm looking forward to see you in the course!


You will have access to all the resources used in this course.

Content

Introduction To Neural Network

Path to Deep Learning
Introduction to Neural Networks
Introduction to Activation functions
Sigmoid and Tanh Activation Functions
Relu, and Leaky Relu, Activation Functions
When to use Sigmoid and Softmax
Introduction to Gradient Descent
Batch vs Stochastic Gradient Descent
Introduction to Optimizers
Dropout and why do we need it
Hyper parameter Tuning in Neural Networks
Introduction to Batch Normalization
Introduction to Tensorflow 2.0 Part 1
Introduction to Tensorflow 2.0 Part 2
Implementing a basic neural network
Improving a Neural network
Quiz on Introduction To Neural Network

Convolution Neural Network

Introduction to Convolution Neural Network
Convolution Operation in CNN
Padding and Pooling
Data Augmentation
Understanding CNN end to end
Implementing Data Processing on Image Data
Implementing CNN using Tensorflow
Introduction to CNN Architectures
Introduction to Transfer Learning
Implementing ResNet and Inception Network
Industry relevance
Quiz on Convolution Neural Network

Recurrent Neural Network

Introduction to RNN
Implementing RNN using Tensorflow
Vanishing and Exploding Gradients
Introduction to LSTMs
Implementing GRU and LSTM using Tensorflow
Introduction to Bidirectional Networks
Implementing BiGRU and BiLSTM
Industry relevance of RNNs

Detecting Pneumonia from Chest X-rays

Understanding the Dataset
Understanding the Problem Statement
Setting up environment
Getting and Parsing Dataset
Loading and Transforming Image Data
Creating a Tensorflow Dataset Object
Introduction to ResNet
Building a Tensorflow Model
Understanding Model Checkpoints
Training the Model
Interpreting the Results
Saving the Trained Model
Evaluating the Model on Test Data
More things to try
Summary
Quiz on Detecting Pneumonia from Chest X-rays

Fruits Identification System

Understanding the Dataset
Understanding the Problem Statement
Setting up the Environment
Processing the Image Data
Applying Data Augmentation
Trying Different Models
Evaluating Model on the Test Data
Real Time Prediction using CNN Models
Summary
Quiz on Fruits Identification System

Stock Market Prediction

Understanding the Stock Market
Understanding the problem Statement
Setting up the Environment
Fetching the Stock Market Data
Understanding the Stock Market Data
Understanding the Trends within the Data
Processing the stock Market Data
Forecasting with LSTMs
Visualizing predictions
Scraping Extra Features for Modelling
Re-Training the LSTMs
Possible Improvements
Quiz on Stock Market Prediction

Face Expression Recognizer

Understanding the Problem Statement
Understanding the Dataset
Setting up the Environment
Parsing Image Dataset
Loading and Augmenting Image Data
Training the Model
Evaluating Model and Saving Objects
Setting up local environment
Using Tensorflow and OpenCV realtime prediction (Part - 1)
Using Tensorflow and OpenCV realtime prediction (Part - 2)
Project Summary
Quiz on Face Expression Recognizer

Outro Section

Conclusion
How to Get Your Certificate of Completion

Bonus Section

Bonus Lecture

Screenshots

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Reviews

Satyam
May 20, 2023
i didnt like this course. she is rushing too much and i even didnt get everything what she is teaching. i really didnt like her teaching. looks like she is teaching for free
Alberto
January 3, 2023
Very well explained until now. I like it and would recommend it to others. The only weak point is some missing or not up-to-date datasets.
Shahinda
November 17, 2022
Great effort is put into this course, though not all code is not explained in detail, as she mostly explains each function's job instead of explaining it line by line. Overall Good.
Daniel
September 25, 2022
Well explained, couldn't be any better. Perfection. Very good job from the instructor. Congratulations.
Nitin
September 25, 2022
Excellent course. This was a great foundational course for deep learning that covered a broad range of topics. The explanations and examples really makes you understand the topics. Videos are well presented and are informative. I recommend this to all Data scientist aspirants.
Syed
September 11, 2022
Loved this course!!! I love the way this course has been made so interactive. So much to learn and practice. The instructor has covered almost everything to do with Deep Learning. So much to explore. Thank you for the fruitful tutorial content.
Arun
July 25, 2022
The course on Deep learning is excellent. The starts from the basics and then it covers advanced concepts in deep learning. The course content and explanation is superb. I personally loved all the theory and intuition lectures. I recommend this course for you if you want to learn deep learning from scratch.
Rida
July 12, 2022
This course is excellent. Very in-depth and fascinating. I learned a lot and have been able to apply some of these principles. Its very helpful and nice course to learn deep learning concepts along with codes. Instructor did a superb job to explain the concept precisely with practical project exercises.
Shivam
June 26, 2022
Great course so far. The instructor explained the topic really well and connected the dots of why we use what we use. Concepts are clearly explained and make me feel easy to learn Deep Learning! Highly recommended for beginners as well as people who would like to revise their knowledge. Thank You!
Piyush
June 25, 2022
This was an amazing course for Deep Learning. The course covers fundamental concepts and building blocks of deep learning and neural networks. I have really enjoyed the course and it's very well structured. It was the best in-depth overview of deep learning. I recommend this to all Data scientist asipirants.
Gregg
February 28, 2022
I want an immediate refund. Your country just voted to abstain from the United Nation's vote to condemn the Russian invasion of Ukraine. That is appalling and I do not want to do business with any entity from India. Your nation should be ashamed of themselves!
Gaurav
December 29, 2021
Excellent course, really helped me a lot to learn new things that I did not know before. Very helpful Indeed !!!!!!!!!
Omar
December 28, 2021
very helpful course each topic is well presented with clearly slides also helps in completing the picture
Margaret
October 6, 2021
Love this persons videos. They are always well laid out, easy to understand and informative. Highly recommend
Nagu
October 6, 2021
The way you explaining the Introduction of the neural network is amazing. It's clear to understand. Thanks.

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4181880
udemy ID
7/13/2021
course created date
7/18/2021
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