Natural Language Processing: Machine Learning NLP In Python

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Price: 199.99$

This course takes you from a beginner level to being able to understand NLP concepts, linguistic theory, and then practice these basic theories using Python – with very simple examples as you code along with me. Get experience doing a full real-world workflow from Collecting your own Data to NLP Sentiment Analysis using Big Datasets of over 50,000 Tweets. Data collection: Scrape Twitter using: OSINT – Open Source Intelligence Tools: Gather text data using real-world techniques. In the real world, in many instances you would have to create your own data set; i. e source your data instead of downloading a clean, ready-made file online Use Python to search relevant tweets for your study and NLP to analyze sentiment. Language Syntax: Most NLP courses ignore the core domain of Linguistics. This course explains the fundamentals of Language Syntax & Parse trees – the foundation of how a machine can interpret the structure of s sentence. New to Python: If you are new to Python or any computer programming, the course instructions make it easy for you to code together with me. I explain code line by line. No Installs, we go straight to coding – Code using Google Colab – to be up-to-date with what’s being used in the Data Science world 2021! The gentle pace takes you gradually from these basics of NLP foundation to being able to understand Mathematical & Linguistic (English-Language-based, Non-Mathematical) theories of Deep Learning. Natural Language Processing Foundation Linguistics & Semantics – study the background theory on natural language to better understand the Computer Science applications Pre-processing Data (cleaning) Regex, Tokenization, Stemming, Lemmatization Name Entity Recognition (NER)Part-of-Speech Tagging SQu ADSQu AD – Stanford Question Answer Dataset. Train your Q & A Model on this awesome SQu AD dataset. Libraries: NLTKSci-kit Learn Hugging Face Tensorflow Pytorch Spa Cy Twint The topics outlined below are taught using practical Python projects! Parse Tree Markov Chain Text Classification & Sentiment Analysis Company Name Generator Unsupervised Sentiment Analysis Topic Modelling Word Embedding with Deep Learning Models Closed Domain Question Answering (Like asking questions on many different topics, from Beyonce to Iranian Cuisine)LSTM using Tensor Flow, Keras Sequence Model Speech Recognition Convert Speech to Text Neural Networks This is taught from first principles – comparing Biological Neurons in the Human Brain to Artificial Neurons. Practical project: Sentiment Analysis of Steam Reviews Word Embedding: This topic is covered in detail, similar to an undergraduate course structure that includes the theory & practical examples of: TF-IDFWord2Vec One Hot Encodingglo Ve Deep Learning Recurrent Neural Networks LSTMs Get introduced to Long short-term memory and the recurrent neural network architecture used in the field of deep learning. Build models using LSTMs