Download Udemy – Natural Language Processing with Deep Learning in Python 2019-12

Natural Language Processing with Deep Learning in Python


Natural Language Processing with Deep Learning in Python is a natural language processing course with deep learning in Python published by Yudemy Academy. A complete guide to mining and implementing word2vec, GloVe, word embedding and sentiment analysis with recurrent networks.

In this course we are going to explore NLP (Natural Language Processing) with deep learning. Earlier, you learned about some basics, such as how many NLP problems are just typical machine learning and data science problems, and simple, practical methods like bag-of-word matrices and word documents. These allow us to do very interesting things, such as identifying spam emails, writing poetry, rotating articles, and grouping similar words. In this course I show you how to do more amazing things. In this course, we will learn not only 1, but 4 new architectures.

What you will learn in the course Natural Language Processing with Deep Learning in Python:

  • Understand and implement word2vec.
  • Understand the CBOW method in word2vec.
  • Understand the skip-gram method in word2vec.
  • Understand negative sampling optimization in word2vec.
  • Understand and implement GloVe using gradient descent and alternating least squares.
  • Use recurrent neural networks to label parts of speech.
  • Use recurrent neural networks to identify the named entity.
  • And …

Who is this course suitable for:

  • Students and professionals who want to create word vector representations for various NLP tasks.
  • Students and professionals interested in advanced neural network architectures such as recurrent neural networks
  • Shouldn’t: Anyone who isn’t comfortable with the prerequisites.

Course details

  • Publisher: Yudmi
  • teacher: Lazy Programmer Inc.
  • English language
  • Education level: Intermediate
  • Number of courses: 100
  • Training duration: 12 hours and 49 minutes

Course topics on 12/2022

Course prerequisites

Install Numpy, Matplotlib, Sci-Kit Learn, and Theano or TensorFlow (should be extremely easy by now)
Understand backpropagation and gradient descent, be able to derive and code the equations on your own
Code a recurrent neural network from basic primitives in Theano (or Tensorflow), especially the scan function
Code a feedforward neural network in Theano (or Tensorflow)
Helpful to have experience with tree algorithms


Natural Language Processing with Deep Learning in Python

Course introduction video

Installation guide

After Extract, view with your favorite Player.

English subtitle

Quality: 720p

download link

Download part 1 – 1 GB

Download part 2 – 1 GB

Download part 3 – 406 MB

Password file(s):


2.40 GB

4.6/5 – (2072 points)

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