Deep Learning Bootcamp with 5 Capstone Projects
Learn about Deep Learning - ANN, CNN, RNN, LSTMs along with Real Time Capstone Projects
Ratings 3.66 / 5.00
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.
Who Should Attend!
- This course is for everyone who wants to master Deep Learning skills.
- This course is for students who have already good knowledge of machine learning and have good programming skills.
- Any people who want to create added value to their business by using powerful Deep Learning tools
- Anyone who is not that comfortable with coding but who is interested in Deep Learning and wants to apply it easily on datasets
- Software engineers who are curious about data science and about the Deep Learning buzz and want to get a better understanding of it
