Deep Learning for NLP with TensorFlow

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Price: 34.99$

Natural Language Processing (NLP) is a hot topic into Machine Learning field. This course is an advanced course of NLP using Deep Learning approach. Before starting this course please read the guidelines of the lesson 2 to have the best experience in this course. This course starts with the configuration and the installation of all resources needed including the installation of Tensor Flow 1. X CPU/GPU, Cuda and Keras. You will be able to use your GPU card if you have one, to accelate fastly the training processes of your models. However if you dont have a GPU card you can follow the instructions using Google Colab. After that we are going to review the main concepts of Deep Learning in the Chapter 2 for applying them into the Natural Language Processing field offering you a solid background for the main chapter. In the main Chapter 3 we are going to study the main Deep Learning libraries and models for NLP such as:- Word Embeddings,- Word2Vec,- Glove,- Fast Text,- Universal Sentence Encoder,- RNN,- GRU,- LSTM,- Convolutions in 1D,- Seq2Seq,- Memory Networks,- and the Attention mechanism. This course offers you many examples, with different datasets suchs as:- Google News,- Yelp comments,- Amazon reviews,- IMDB reviews,- the Bible corpus, etc and different text corpus. At the final in Chapter 4 you will put in practice your knowledge with practical applications such as:- Multiclass Sentiment Analysis,- Text Generation,- Machine Translation,- Developing a Chat Bot and more. For coding we are going to use Tensor Flow, Keras, Google Colab and many Python libraries. If you need a previous background in Natural Language Processing or in Machine Learning I recommend you my courses: Python for Machine Learning and Data Mining or Natural Language Processing with Python and NLTKThe student has the opportunity to get a feedback from the instructor through Q & A forums, by email: machine. learning. eirl@gmail. com or by Twitter: @AILearning CQ