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Data Science: Deep Learning and Neural Networks in Python

$94.99 $12.00

4.88 (12 reviews)
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Description

What you’ll learn

  • Learn how Deep Learning REALLY works (not just some diagrams and magical black box code)
  • Learn how a neural network is built from basic building blocks (the neuron)
  • Code a neural network from scratch in Python and numpy
  • Code a neural network using Google’s TensorFlow
  • Describe different types of neural networks and the different types of problems they are used for
  • Derive the backpropagation rule from first principles
  • Create a neural network with an output that has K > 2 classes using softmax
  • Describe the various terms related to neural networks, such as “activation”, “backpropagation” and “feedforward”
  • Install TensorFlow

This course will get you started in building your FIRST artificial neural network using deep learning techniques. Following my previous course on logistic regression, we take this basic building block, and build full-on non-linear neural networks right out of the gate using Python and Numpy. All the materials for this course are FREE.

We extend the previous binary classification model to multiple classes using the softmax function, and we derive the very important training method called “backpropagation” using first principles. I show you how to code backpropagation in Numpy, first “the slow way”, and then “the fast way” using Numpy features.

Next, we implement a neural network using Google’s new TensorFlow library.

You should take this course if you are interested in starting your journey toward becoming a master at deep learning, or if you are interested in machine learning and data science in general. We go beyond basic models like logistic regression and linear regression and I show you something that automatically learns features.

This course provides you with many practical examples so that you can really see how deep learning can be used on anything. Throughout the course, we’ll do a course project, which will show you how to predict user actions on a website given user data like whether or not that user is on a mobile device, the number of products they viewed, how long they stayed on your site, whether or not they are a returning visitor, and what time of day they visited.

Another project at the end of the course shows you how you can use deep learning for facial expression recognition. Imagine being able to predict someone’s emotions just based on a picture!

After getting your feet wet with the fundamentals, I provide a brief overview of some of the newest developments in neural networks – slightly modified architectures and what they are used for.

NOTE:

If you already know about softmax and backpropagation, and you want to skip over the theory and speed things up using more advanced techniques along with GPU-optimization, check out my follow-up course on this topic, Data Science: Practical Deep Learning Concepts in Theano and TensorFlow.

I have other courses that cover more advanced topics, such as Convolutional Neural NetworksRestricted Boltzmann MachinesAutoencoders, and more! But you want to be very comfortable with the material in this course before moving on to more advanced subjects.

This course focuses on “how to build and understand“, not just “how to use”. Anyone can learn to use an API in 15 minutes after reading some documentation. It’s not about “remembering facts”, it’s about “seeing for yourself” via experimentation. It will teach you how to visualize what’s happening in the model internally. If you want more than just a superficial look at machine learning models, this course is for you.

“If you can’t implement it, you don’t understand it”

  • Or as the great physicist Richard Feynman said: “What I cannot create, I do not understand”.

  • My courses are the ONLY courses where you will learn how to implement machine learning algorithms from scratch

  • Other courses will teach you how to plug in your data into a library, but do you really need help with 3 lines of code?

  • After doing the same thing with 10 datasets, you realize you didn’t learn 10 things. You learned 1 thing, and just repeated the same 3 lines of code 10 times…

Suggested Prerequisites:

  • calculus (taking derivatives)

  • matrix arithmetic

  • probability

  • Python coding: if/else, loops, lists, dicts, sets

  • Numpy coding: matrix and vector operations, loading a CSV file

  • Be familiar with basic linear models such as linear regression and logistic regression

WHAT ORDER SHOULD I TAKE YOUR COURSES IN?:

  • Check out the lecture “Machine Learning and AI Prerequisite Roadmap” (available in the FAQ of any of my courses, including the free Numpy course)

Who this course is for:

  • Students interested in machine learning – you’ll get all the tidbits you need to do well in a neural networks course
  • Professionals who want to use neural networks in their machine learning and data science pipeline. Be able to apply more powerful models, and know its drawbacks.

Course content

  • Welcome
  • Review
  • Preliminaries: From Neurons to Neural Networks
  • Classifying more than 2 things at a time
  • Training a neural network
  • Practical Machine Learning
  • TensorFlow, exercises, practice, and what to learn next
  • Project: Facial Expression Recognition
  • Backpropagation Supplementary Lectures
  • Higher-Level Discussion

12 reviews for Data Science: Deep Learning and Neural Networks in Python

  1. Luis Brito

    I can definitely see this course helping breaking through that initial barrier when it comes to learning a programming language. I’m positive I’ll finish it and hopefully master python by then.

  2. Abdallah Galal Abouhussein

    I would like to share my personnel experience, i`m very pleased and happy for taking this impressive course because Dr. Angela always makes it simple and easy to understand and always makes a precaution section before or after any bug that may appear to some students and also write or record the solution for us, and each word she said is very real and easy to understand.
    Thanks Dr. Angela
    Abdallah Galal

  3. Jiaqing Fan

    Very good course. Dr Angela explains things very clearly. The exercises are interactive and helpful.

    Angela’s voice is like ASMR in most lessons. So you won’t lose focus?

  4. Jaime Sánchez Blanco

    Every concept is very well explained so you can assimilate it, and the teacher insists in practicing daily to get the habit of programming. It really motivates to keep studying and practicing every day.

  5. Bradley Carouthers

    3 days in and I’ve already learned more than other training programs where I’ve put months in. Her teaching style is both efficient and effective.

    Edit: Now on day 29 and the course has held up my expectations and hopes. The rise in complexity is not too sharp, and every day feels like an accomplishment. Angela takes her time to explain things without rushing, yet is able to pack tons of information in nuggets of time.

    Still recommend supplemental exposure for a more wholesome grasp. Though, this should be quite enough

  6. Tommy Prévost

    Very good course.

    PROs: lots of coding exercises, clear explanations, great examples, adapted to 2021’s reality.

    CONs: past the first 30 lessons, many similar coding hands-on.

  7. Quang Tu

    I love all the lectures and challenges of this course. I finally find myself in love with coding. This is definitely a fun course. Thank you Angela for this great course.

  8. Fortunate Eze

    This course is nothing short of AMAZING. The level of love and sincere desire to see students succeed present in this course is a rare sight. This course is fun, it’s challenging, it’s suspense-filled, it makes you feel good about yourself solving those challenges. You don’t take this course and memorise codes, you take it and you know what you’re doing because you literally do it yourself.

    It couldn’t possibly be any more obvious that Angela brought out her whole heart, time, energy and resources to give us a course that if priced based on it’s value, many of us certainly can’t afford. I mean, she kept advising and encouraging us to keep going, because she knows the road could get bumpy, she made a few jokes and used funny animations so we smile along the way keeping it fun. Why some people can’t see this and would rather subscribe to trying to bend courses to fit their own personal preferences is beyond me, but I guess people will always be people.

    Dear Angela, I cannot speak for everyone but I certainly can speak for myself and I’m saying thank you. The efforts you put into making this course outstanding didn’t go unnoticed.

    Let as many of us as appreciate your efforts make you happy and energize you to create more life changing courses for us.

    Cheers.

  9. Chendaniel

    Just the course fits me. Learn by doing, it is easy to start and just follow the flow and at day 15 you realized how to program in Python. Then the magic happen. I am on day 27 and I am looking forward to start a new section everyday.

  10. Caspar Cheng

    Angela is my favourite teacher on Udemy, her courses always come with clear and concise demonstration, make it really easy to understand the content. Meanwhile, she also provide a lot of tips to encourage us moving further on the way of coding. I’m definitely a super fan of her. I had finished her web development boot camp and now I’m learning Python 100 days of code. This course is amazing as she provided one particular project for each day’s learning, which is, really useful and handy. Also, those projects are really interesting and won’t let me feel disappointed about myself. Although some of them are a little bit difficult, they’re still resolvable after some struggling and searching online. I’ll recommend this course for those who really want to learn Python well and write real python projects from scratch!

  11. Jonas Weber

    The course was awesome in the first half! Really helped me to get back to programming and learning new techniques. Also the course got way to much focused on web development in the second half, which I’m not really interested in and is redundand to your dedicated web development course. The lack of videos in the last quarter was rather sad. I really would’ve liked some video explanations for pandas and matplotlib. The challenges and capstone projects were great and challenging!
    All in all I can really recommend this course for beginners and those who want to learn python and/or get back to programming!

  12. Rohit Prasad

    Angela is the best teacher I have ever experienced. The way she explains all the topics and makes use of it in the projects is commendable. Thank you so much Angela for this course.

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