Data Science Deep Learning in Python

What Does The Course Offer?

This course will offer you hands-on knowledge of the fundamentals of data science. You will learn to build your first artificial neural network with the help of deep learning techniques.

We will take logistic regression as a building block and build non-linear neural networks straight out of the gate with Numpy and Python. The best part is that all the materials for this course are free of cost.

Our multiple classes are an extension of the previous binary classification model using the softmax function. With the help of the first principles, we derive the essential training method “backpropagation.” Your course will begin with learning how to code backpropagation in Numpy “the slow way”, and then gradually, we will move to “the fast way” with Numpy features.

After that, we implement a neural network with Google’s new TensorFlow library. If you want to become a pro at machine learning and data science, you should definitely consider enrolling in this course.

Our curriculum is not just limited to basic models like logistic regression and linear regression. Instead, we go above and beyond to facilitate you and enlighten you with the deep knowledge of data sciences.

This course promises you tons of practical examples so you can implement what you learn. During the course, we will conduct course projects to teach you real-life predictions. One of the projects will teach you how to predict user actions on a website when you are provided with the user’s data. You will learn to predict:

• If the user had a mobile device
• The number of products the user saw
• How long did they stay on the site
• What time of the day did the user visit
• Are they a returning visitor or not

The course will include another project as you reach the end. It will show you how to use your learning for facial expression recognition. If you think about it, after you have finished, you will be able to predict a person’s emotion based on just a picture! Isn’t it fascinating?

Once you are done and dusted with the basics, we will provide you with a brief overview of some new developments in neural networks. This will include somewhat modified structures and their applications.

Here, we would like to make a note that if you are already familiar with softmax and backpropagation and want to skip the theory to speed up your learning process, you can check out the follow-up courses where you can learn advanced techniques with GPU optimisation.

Additional Courses for Advanced Levels

We have some other courses to cover some advanced level topics, such as:

• Convolutional Neural Networks
• Restricted Boltzmann Machines
• Autoencoders

If you have developed a strong understanding of the previous course, you can move forward with advanced topics!