Modern Natural Language Processing (NLP) using Deep Learning.

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Modern Natural Language Processing(NLP) using Deep Learning.

Modern Natural Language Processing (NLP) using Deep Learning Course

Implement Sentiment Analysis, Speech Recognition, Translation, Question Answering & Question Answering with TensorFlow 2

In this course, we shall look at core Deep Learning concepts and apply our knowledge to solve real world problems in Natural Language Processing using the Python Programming Language and TensorFlow 2. We shall explain core Machine Learning topics like Linear Regression, Logistic Regression, Multi-class classification and Neural Networks. If you’ve gotten to this point, it means you are interested in mastering Deep Learning For NLP and using your skills to solve practical problems.

You may already have some knowledge on Machine learning, Natural Language Processing or Deep Learning, or you may be coming in contact with Deep Learning for the very first time. It doesn’t matter from which end you come from, because at the end of this course, you shall be an expert with much hands-on experience. You shall work on several projects like Sentiment Analysis, Machine Translation, Question Answering, Image captioning, speech recognition and more, using knowledge gained from this course.

Best Seller CourseDeep Learning Prerequisites: Logistic Regression in Python

What you’ll learn

  • Introductory Python, to more advanced concepts like Object Oriented Programming, decorators, generators, and even specialized libraries like Numpy & Matplotlib
  • Mastery of the fundamentals of Machine Learning and The Machine Learning Developmment Lifecycle.
  • Linear Regression, Logistic Regression and Neural Networks built from scratch.
  • TensorFlow installation, Basics and training neural networks with TensorFlow 2.
  • Convolutional Neural Networks, Modern ConvNets, training object recognition models with TensorFlow 2.
  • Recurrent Neural Networks, Modern RNNs, training sentiment analysis models with TensorFlow 2.
  • Neural Machine Translation, Question Answering, Image Captioning, Sentiment Analysis, Speech recognition
  • Deploying a Deep Learning Model with Google Cloud Function.

You May Also Need This CoursePyTorch: Deep Learning and Artificial Intelligence


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