Natural Language Processing with Deep Learning in Python –Udemy
Previously, you learned about some of the fundamentals, such as how many NLP problems are simply disguised machine learning and data science problems, and simple, practical methods such as bag-of-words and term-document matrices. These enabled them to do some pretty cool things, such as detect spam emails, write poetry, spin articles, and group similar words together.
This course will teach you NLP (natural language processing) using deep learning. This course will teach you about word2vec and how to use it. You will also learn how to use gradient descent and alternating least squares to implement GloVe. For named entity recognition, this course employs recurrent neural networks. You will also learn how to build recursive neural tensor networks for sentiment analysis. Let's take a look at the topics covered in this course.
Topics Covered
- Outline, Review, and Logistical Things.
- Beginner’s corner- Working with word vectors.
- Review of Language Modeling and Neural Networks.
- Word Embedding and Word2Vec.
- Word Embedding using GloVe.
- Unifying Word2Vec and GloVe.
- Using a Neural Network to solve NLP problems.
- Recursive Neural Network
- Theano and Tensorflow Basics Review.
Extra Benefits
- You will get a Certificate of Completion.
- Along with that, you will get full-time access to course material.
Who Should Enroll?
- Those who have knowledge of calculus, matrix addition, multiplication, and, probability and comfortable with Python coding, and Numpy coding.
- If someone has knowledge of neural networks and backpropagation.
- Those who can write feedforward neural network in Theano or TensorFlow and recurrent neural network / LSTM /
- GRU in Theano or TensorFlow.
Interested to Enroll?
- If yes, then get more details here- Natural Language Processing with Deep Learning in Python
Rating: 4.5/5.0
Provider: Lazy Programmer
Time to Complete- 12 hours
Enroll here: udemy.com/course/natural-language-processing-with-deep-learning-in-python
