Deep Learning with TensorFlow 2

with Iskren Vankov and Iliya Valchanov

Helping you learn and practice advanced deep learning techniques with TensorFlow 2.0 code and syntax. Complete with new TF2 exercises and projects.

6 hours 83 lessons
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83 High Quality Lessons
28 Practical Tasks
6 Hours of Content
Certificate of Achievement

Course Overview

Machine and deep learning are some of those quantitative analysis skills that differentiate the data scientist from the other members of the team. Not to mention that the field of machine learning is the driving force of artificial intelligence. This course will teach you how to leverage deep learning and neural networks for the purposes of data science. The technology we employ is TensorFlow 2.0, which is the state-of-the-art deep learning framework.

Topics covered

machine learningMathematicsProgrammingPythonTheory

What You'll Learn

This course will teach you the inner workings of deep neural networks with emphasis on the why and how of things. You will see the theory implemented in practice with the powerful framework TensorFlow 2.0.

Grasp the mathematics behind deep learning algorithms 
Understand backpropagation, stochastic gradient descent, batching 
Build ML algorithms from scratch in Python 
Carry out pre-processing, standardization, normalization, and one-hot encoding 
Grasp overfitting and combat it with early stopping 
Hands on experience with TensorFlow 2 


Student feedback


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It's fun to learn this stuff, I guess, but I don't love that it's narrated by a speech-to-text bot who sounds way too happy and is almost kind of screaming everything at me and mispronouncing "Oxford" and "eta". The visuals are okay except for when there's a cartoon representation of the "instructor" with his lips moving and they don't match the words. I looked the guy up and he's just some self-taught dude with a degree. Doesn't even consider himself a teacher -- just a "content creator" for this site. If I was paying for this, I'd be extremely disappointed.
The course exceeded my expectations and provided a structured approach to develop NN's in Tensorflow. I established the individual concepts followed by connecting the dots(big picture) and thereby giving the learners with a process as a result. A big thumbs up to the team. The one thing I personally felt is that it came off a very math lite. If another course solely dedicated to the Mathematics behind these algorithms could be developed then we could have it as a powerful weapon in our arsenal.
Theory was fundamental to understanding the course. The instructor went into a good enough detail with the theory. The issue with that approach is the "robotic voiceover." Hearing too much of the robotic voice made the process of completing the theory daunting. I recommend the theoretical be explained with a normal voice over.
Good introduction to Deep learning course. This course provided both theory and coding using tensorflow and jupyter notebook. If you are new to this area, this course is very helpful to make you understand the idea of this field.
The teacher teaching style is like a TV news caster, continuously reading with a single tone, seems like he is in hurry to quickly finish. Sorry for my comments, but that's what I observe it. Anyhow contents are good.
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Iskren Vankov

“If you need real world practice on how to use deep learning to optimize business performance, this is the course for you. I’ve made sure to give you plenty of opportunities to implement cutting edge optimizations, get hands on with TensorFlow 2 and even build your very own algorithm and put it through training!”

Iskren Vankov

Microsoft Research Award

Deep Learning with TensorFlow 2

with Iskren Vankov and Iliya Valchanov

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