New Course! Convolutional Neural Networks with TensorFlow in Python

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Nikola Pulev 20 Oct 2021 3 min read

Convolutional beural networks with tensorflow in python course

Hi! My name is Nikola Pulev. I am a Physics graduate from the University of Cambridge with a passion for mathematics, programming, and Machine Learning. My skillset and professional interests set the stage for my career as an instructor at 365 Data Science… And today, I am extremely happy to announce the release of our new course -Convolutional Neural Networks with TensorFlow in Python!

I wrote this post to share with you what makes this course one-of-a-kind and what sought-after skills it will help you develop. In the end, I’ll tell you a bit more about myself and the projects I’ve worked on at 365 Data Science.

Why Convolutional Neural Networks?

Convolutional Neural Networks (CNNs) are a subtype of deep neural networks. These networks are extensively used in the field of Computer Vision, as they specialize in inferring information from spatial-structure data to help computers gain high-level understanding from digital images and videos. Tasks can range from the simple classification of an image as a dog or a cat to super-complex applications as is the case with self-driving cars, for example.

Right now, this is where most of the active Machine Learning research is concentrated, and CNNs are a crucial part of it, which means it is the best time to up your game and master this piece of the Deep Learning puzzle.

And this course is exactly what you need to gain insights into the rapidly expanding field of Machine Learning and Computer Vision through the use of Convolutional Neural Networks.

Who Is This Course for?

This course is a great match for you if you want to advance your skills in Machine Learning and Computer Vision and learn how Convolutional Neural Networks work. Whether you’re interested in a career in Deep Learning, or you are just curious and passionate about AI, you will find the theory and hands-on practice that will help you reach your goals.

What Is the Structure of the Convolutional Neural Networks Course?

The course comprises 52 lessons, a myriad of assignments, homework, downloadable files and notebooks, as well as quiz questions and course notes.

But that’s not all. I believe that practice makes perfect, that’s why I’ve also included a comprehensive practical example of a real-world project with 16,000 images from a fashion industry dataset.

That’s how I made sure that by the end of this course, you will be completely equipped with all the tools you need to confidently work on CNN projects.

If you’d like to explore all topics in the course curriculum, you can find them on the Convolutional Neural Networks with TensorFlow in Python course page.

What Will You Learn?

The idea of this course is to give you the real CNN experience.

You will:

  • Learn the fundamentals of Convolutional Neural Networks
  • Perform Computer Vision and Machine Learning tasks
  • Master working with TensorFlow and Tensorboard
  • Understand kernels
  • Get the hang of convolution and its role in CNNs
  • Get familiar with L2 regularization and weight decay
  • Grasp the concept of dropout
  • Visualize networks and metrics using TensorBoard
  • Approach multilabel classification
  • Gain experience from a big real-world practical example
  • Convert Images into Tensors
  • Explore the concepts behind popular state-of-the-art CNN architectures
  • Master and apply 3 common techniques to improve the performance of your models
  • Dive into the workings of some popular CNN architectures

About the Author

As I mentioned, I am a Natural Sciences graduate from the University of Cambridge, in the UK. I truly enjoy mathematics, physics, and programming and I’ve participated in multiple national and international competitions, where I’ve won numerous awards. I also hold a silver medal from the International Physics Olympiad. However, I am not doing much Physics at present. I am dedicated to creating data science courses to help anyone advance in the field, regardless of their background. I believe that you don’t need a degree to master a particular area. All you need is passion and a little guidance.

Convolutional Neural Networks with TensorFlow in Python Course is part of the 365 Data Science Program, so enrolled students can access the courses at no extra cost.

Not a current subscriber? You can try the Convolutional Neural Networks with TensorFlow in Python Course for free!

Nikola Pulev

Instructor at 365 Data Science

Nikola Pulev is a University of Cambridge graduate, a data science practitioner, and instructor at 365 Data Science. An expert in Python modeling, Programming, and Mathematical Modeling, his courses have helped thousands of students master advanced topics of Web Scraping and API Fundamentals in Python and Convolutional Neural Networks with TensorFlow in Python.