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Deep Learning: Recurrent Neural Networks in Python – Udemy

(10 customer reviews)

$18

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Description

What you’ll learn

  • Apply RNNs to Time Series Forecasting (tackle the ubiquitous “Stock Prediction” problem)
  • Apply RNNs to Natural Language Processing (NLP) and Text Classification (Spam Detection)
  • Apply RNNs to Image Classification
  • Understand the simple recurrent unit (Elman unit), GRU, and LSTM (long short-term memory unit)
  • Write various recurrent networks in Tensorflow 2
  • Understand how to mitigate the vanishing gradient problem

*** NOW IN TENSORFLOW 2 and PYTHON 3 ***

Learn about one of the most powerful Deep Learning architectures yet!

The Recurrent Neural Network (RNN) has been used to obtain state-of-the-art results in sequence modeling.

This includes time series analysis, forecasting and natural language processing (NLP).

Learn about why RNNs beat old-school machine learning algorithms like Hidden Markov Models.

This course will teach you:

  • The basics of machine learning and neurons (just a review to get you warmed up!)

  • Neural networks for classification and regression (just a review to get you warmed up!)

  • How to model sequence data

  • How to model time series data

  • How to model text data for NLP (including preprocessing steps for text)

  • How to build an RNN using Tensorflow 2

  • How to use a GRU and LSTM in Tensorflow 2

  • How to do time series forecasting with Tensorflow 2

  • How to predict stock prices and stock returns with LSTMs in Tensorflow 2 (hint: it’s not what you think!)

  • How to use Embeddings in Tensorflow 2 for NLP

  • How to build a Text Classification RNN for NLP (examples: spam detection, sentiment analysis, parts-of-speech tagging, named entity recognition)

All of the materials required for this course can be downloaded and installed for FREE. We will do most of our work in Numpy, Matplotlib, and Tensorflow. I am always available to answer your questions and help you along your data science journey.

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.

See you in class!

“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:

  • matrix addition, multiplication

  • basic probability (conditional and joint distributions)

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

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

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, professionals, and anyone else interested in Deep Learning, Time Series Forecasting, Sequence Data, or NLP
  • Software Engineers and Data Scientists who want to level up their career

Course content

  • Welcome
  • Google Colab
  • Machine Learning and Neurons
  • Feedforward Artificial Neural Networks
  • Recurrent Neural Networks, Time Series, and Sequence Data
  • Natural Language Processing (NLP)
  • In-Depth: Loss Functions
  • In-Depth: Gradient Descent
  • Extras
  • Setting Up Your Environment (FAQ by Student Request)

10 reviews for Deep Learning: Recurrent Neural Networks in Python – Udemy

  1. Donny Phan

    Super practical. Lessons are catered towards anyone looking to find work in this industry. It felt very comprehensive and gave me a broad understanding of the programming spectrum

  2. Madhav raj Verma

    Thanks for your great effort. i am fully satisfied with this course the way you teach and your explanation are very clear ,The content you provide in your course no one can do this at this price.

  3. Sachin Gupta

    I really didn’t want to leave a low rating as Angela is a great teacher. The 1st half of this course was terrific. The 2nd half was terrible. Under the justification of “teaching students how to figure things out on their own”, pretty much all videos and all explanations were dropped. You were just told what to do, given links to documentation and told to figure it out on your own. I understand doing that to some degree, but to revert to that entirely for nearly half the content barely makes this a course. It’s just a list of things for you to learn, then you’re left on your own to learn them. The 2nd half was so bad, especially the data science component, that I didn’t bother finishing the course.

  4. Vincent Beaudet

    Amazing 40 days course.
    Angela is a great teacher.
    The other 60 days are all about web developement, interacting with web pages, on your own with little to no explanations. I did not expect that at all. I wanted to learn more about software and scripting.
    This left me disappointed , confused and i started to doubt myself. Not a fun experience after the amount of effort i’v put in this course.

    Exercices format and explanations for the first 40 days were worth it tho.

  5. Ben K

    Not just an introduction to python, but really helps you learn fundamental aspects of python and coding in general. Some parts may require some knowledge on the subject (data science comes to mind) and there is quite some web development in the course. So, a few areas were not completely to my liking (I would have liked to see it done differently), but this course deserves the 5 stars in my opinion.

  6. Omid Alikhel

    I found the method a bit difficult when a code is written and then changed back to something different, with no enough explanation of how something happened and where it came from or a step by step explanation of why something is happening, i have no doubt in the instructors talent, but we are beginners!

  7. Devang Jain

    The course is not updated and most of the solution codes don’t work and there are no video solutions towards the end

  8. Szymon Kozak

    I think that the course tutor is really good in giving right information to learn at the right time. Thanks to this fact, my understanding of coding in python after 29 days of learning is above my expectations.

  9. Begoña Ruiz Diaz

    Ha sido la mejor elección que podría haber hecho.

  10. Vaibhav Sachdeva

    I want to thank Angela for making such an amazing course. It really helped me explore more things with python.

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