Deep Neural Networks using Python for Absolute Beginners

Are you ready to start your path to becoming a Deep Learning expert?

Are you ready to train your machine like a father teaches his son?

There are lots of courses and lectures out there regarding DNNs. This course is different!

This course is truly step-by-step. In every new tutorial, we build on what had already learned and move one extra step forward, and then we assign you a small task that is solved at the beginning of the next video.

We start by teaching the theoretical part of the concept, and then we implement everything as it is practically using Python.

This comprehensive course will be your guide to learning how to use the power of Python to train your machine such that your machine starts learning just like humans, and based on that learning, your machine starts making predictions as well!

We’ll be using Python as a programming language in this course, which is the hottest language nowadays if we talk about machine learning. Python will be taught from the elementary level up to an advanced level so that any machine learning concept can be implemented.

We’ll also learn various steps of data preprocessing, which allows us to make data ready for machine learning algorithms.

We’ll learn all general concepts of machine learning overall, which will be followed by the implementation of one of the essential ML algorithms, “Deep Neural Networks.” Each concept of DNNs will be taught theoretically and will be implemented using Python.

Machine learning has been ranked as one of the hottest jobs on Glassdoor, and the average salary of a machine learning engineer is over $110,000 in the United States, according to Indeed! Machine Learning is a rewarding career that allows you to solve some of the world's most interesting problems!

This course is designed for both beginners with some programming experience or even those who know nothing about ML and DNNs!

This comprehensive course is comparable to other Machine Learning courses that usually cost thousands of dollars, but now you can learn all that information at a fraction of the cost! With over 6 hours of HD video lectures that are divided into over 85 videos and detailed code notebooks for every address, this is one of the most comprehensive courses for Deep Neural Networks and machine learning on Udemy!

Why Should You Enroll in This Course?

The course is crafted to help you understand not only how to build RNNs but also how to train them. This straightforward learning by doing the course will help you in mastering the concepts and methodology with regard to Python. 

This course is:

• Easy to understand.
• Expressive and self-explanatory.
• To the point. 
• Practical with live coding.
• Thorough, covering the most advanced and recently discovered RNN models by renowned data scientists.

Teaching Is Our Passion:

We focus on creating online tutorials that encourage learning by doing. We aim to provide you with more than a superficial look at DNNs. For instance, the project in the final module will help you to see for yourself via experimentation the practical implementation of DNNs in the real world. We have worked extra hard to ensure you understand the concepts clearly. We want you to have a sound understanding of the basics before you move onward to the more complex concepts. The course materials that make certain you accomplish all this include high-quality video content, course notes, meaningful course materials, handouts, and evaluation exercises. You can also get in touch with our friendly team in case of any queries.

Course Content:

We'll teach you how to program with Python, and how to use it for data preprocessing and DNNs! Here are just a few of the topics that we will be learning:

• Programming with Python
• NumPy with Python for array handling
• Using pandas Data Frames to handle Excel Files
• Data Preprocessing
• Machine Learning concepts, including Basics of ML, Gradient descent, Logistic Regression, Feed Forward, Back Propagation, Model optimization, etc.
• DNNs from absolute scratch using NumPy
• Implementing DNNs on different data sets
• How can we use DNN for IRIS classification, and much more?

Enroll in the course and become a data scientist today!

After completing this course successfully, you will be able to:

• Relate the concepts and theories of sequence modeling with DNNs.
• Understand the methodology of DNNs with Data Science using real datasets.

Who this course is for:

• People who want to take their data speak to the next level.
• People who want to master DNNs with real datasets in Data Science.
• People who want to implement DNNs in realistic projects.
• Individuals who are passionate about numbers and programming.
• Business Analysts.
• Data Scientists.