Download and Learn Become a Natural Language Processing Expert Udacity Nanodegree Course 2023 for free with google drive download link.

Master the skills to get computers to understand, process, and manipulate human language. Build models on real data, and get hands-on experience with sentiment analysis, machine translation, and more.

Estimated time

3 Months

At 10-15 hrs/week

In collaboration with

Amazon Alexa

IBM Watson

What You’ll Learn in Become a Natural Language Processing Expert Nanodegree

Master Natural Language Processing

Learn cutting-edge natural language processing techniques to process speech and analyze text. Build probabilistic and deep learning models, such as hidden Markov models and recurrent neural networks, to teach the computer to do tasks such as speech recognition, machine translation, and more!

Work on a variety of natural language processing techniques. Build models using probabilistic and deep learning techniques and apply them to speech recognition, machine translation, and more!

Prerequisite Knowledge

This program requires experience with Python, statistics, machine learning, and deep learning.

  • You need to have intermediate to advanced Python experience. You are familiar with object-oriented programming. You can write nested for loops and can read and understand code written by others.
  • Intermediate statistics background. You are familiar with probability.
  • Intermediate knowledge of machine learning techniques. You can describe backpropagation, and have seen a few examples of neural network architecture (preferrably a recurrent neural network or a long short-term memory network).
  • You have seen or worked with a deep learning framework like TensorFlow, Keras, or PyTorch before.

Introduction to Natural Language Processing

Learn text processing fundamentals, including stemming and lemmatization. Explore machine learning methods in sentiment analysis. Build a speech tagging model.

Project – Part of Speech Tagging

Use several techniques, including table lookups, n-grams, and hidden Markov models, to tag parts of speech in sentences, and compare their performance.

Computing with Natural Language

Learn advanced techniques like word embeddings, deep learning attention, and more. Build a machine translation model using recurrent neural network architectures.

Project – Machine Translation

Build a deep neural network that functions as part of an end-to-end machine translation pipeline. Your completed pipeline will accept

English text as input and return the French translation. You’ll be able to explore several recurrent neural network architectures and compare their performance.

Communicating with Natural Language

Learn voice user interface techniques that turn speech into text and vice versa. Build a speech recognition model using deep neural networks.

Project – Speech Recognizer

Build a deep neural network that functions as part of an end-to-end automatic speech recognition (ASR) pipeline. The model will convert raw audio into feature representations, which will then turn them into transcribed text.

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The Natural Language Processing market is predicted to reach $22.3 billion by 202

Become a Natural Language Processing Expert Nanodegree Free Download Link: