IIRF Online > Development > Data Science > Natural Language Processing > Machine Learning: Natural Language Processing in Python (V2)
Machine Learning: Natural Language Processing in Python (V2) by Udemy
NLP: Use Markov Models, NLTK, Artificial Intelligence, Deep Learning, Machine Learning, and Data Science in Python
Course Highlights
- How to convert text into vectors using CountVectorizer, TF-IDF, word2vec, and GloVe
- How to implement a document retrieval system / search engine / similarity search / vector similarity
- Probability models, language models and Markov models (prerequisite for Transformers, BERT, and GPT-3)
- How to implement a cipher decryption algorithm using genetic algorithms and language modeling
- How to implement spam detection
- How to implement sentiment analysis
- How to implement an article spinner
- How to implement text summarization
- How to implement latent semantic indexing
- How to implement topic modeling with LDA, NMF, and SVD
- Machine learning (Naive Bayes, Logistic Regression, PCA, SVD, Latent Dirichlet Allocation)
- Deep learning (ANNs, CNNs, RNNs, LSTM, GRU) (more important prerequisites for BERT and GPT-3)
- Hugging Face Transformers (VIP only)
- How to use Python, Scikit-Learn, Tensorflow, +More for NLP
- Text preprocessing, tokenization, stopwords, lemmatization, and stemming
- Parts-of-speech (POS) tagging and named entity recognition (NER)
Skills you will learn!
Curriculum
2 Topics
Introduction and Outline
Are You Beginner Intermediate or Advanced? All are OK!
5 Topics
Get Your Hands Dirty Practical Coding Experience Data Links
How to use Github & Extra Coding Tips (Optional)
Where to get the code notebooks and data
How to Succeed in This Course
Temporary 403 Errors
22 Topics
Vector Models & Text Preprocessing Intro
Basic Definitions for NLP
What is a Vector?
Bag of Words
Count Vectorizer (Theory)
Tokenization
Stopwords
Stemming and Lemmatization
Stemming and Lemmatization Demo
Count Vectorizer (Code)
Vector Similarity
TF-IDF (Theory)
(Interactive) Recommender Exercise Prompt
TF-IDF (Code)
Word-to-Index Mapping
How to Build TF-IDF From Scratch
Neural Word Embeddings
Neural Word Embeddings Demo
Vector Models & Text Preprocessing Summary
Text Summarization Preview
How To Do NLP In Other Languages
Suggestion Box
1 Topic
Probabilistic Models (Introduction)
13 Topics
Markov Models Section Introduction
The Markov Property
The Markov Model
Probability Smoothing and Log-Probabilities
Building a Text Classifier (Theory)
Building a Text Classifier (Exercise Prompt)
Building a Text Classifier (Code pt 1)
Building a Text Classifier (Code pt 2)
Language Model (Theory)
Language Model (Exercise Prompt)
Language Model (Code pt 1)
Language Model (Code pt 2)
Markov Models Section Summary
6 Topics
Article Spinning - Problem Description
Article Spinning - N-Gram Approach
Article Spinner Exercise Prompt
Article Spinner in Python (pt 1)
Article Spinner in Python (pt 2)
Case Study: Article Spinning Gone Wrong
13 Topics
Section Introduction
Ciphers
Language Models (Review)
Genetic Algorithms
Code Preparation
Code pt 1
Code pt 2
Code pt 3
Code pt 4
Code pt 5
Code pt 6
Cipher Decryption - Additional Discussion
Section Conclusion
1 Topic
Machine Learning Models (Introduction)
6 Topics
Spam Detection - Problem Description
Naive Bayes Intuition
Spam Detection - Exercise Prompt
Aside: Class Imbalance ROC AUC and F1 Score (pt 1)
Aside: Class Imbalance ROC AUC and F1 Score (pt 2)
Spam Detection in Python
7 Topics
Sentiment Analysis - Problem Description
Logistic Regression Intuition (pt 1)
Multiclass Logistic Regression (pt 2)
Logistic Regression Training and Interpretation (pt 3)
Sentiment Analysis - Exercise Prompt
Sentiment Analysis in Python (pt 1)
Sentiment Analysis in Python (pt 2)
10 Topics
Text Summarization Section Introduction
Text Summarization Using Vectors
Text Summarization Exercise Prompt
Text Summarization in Python
TextRank Intuition
TextRank - How It Really Works (Advanced)
TextRank Exercise Prompt (Advanced)
TextRank in Python (Advanced)
Text Summarization in Python - The Easy Way (Beginner)
Text Summarization Section Summary
9 Topics
Topic Modeling Section Introduction
Latent Dirichlet Allocation (LDA) - Essentials
LDA - Code Preparation
LDA - Maybe Useful Picture (Optional)
Latent Dirichlet Allocation (LDA) - Intuition (Advanced)
Topic Modeling with Latent Dirichlet Allocation (LDA) in Python
Non-Negative Matrix Factorization (NMF) Intuition
Topic Modeling with Non-Negative Matrix Factorization (NMF) in Python
Topic Modeling Section Summary
5 Topics
LSA / LSI Section Introduction
SVD (Singular Value Decomposition) Intuition
LSA / LSI: Applying SVD to NLP
Latent Semantic Analysis / Latent Semantic Indexing in Python
LSA / LSI Exercises
1 Topic
Deep Learning Introduction (Intermediate-Advanced)
7 Topics
The Neuron - Section Introduction
Fitting a Line
Classification Code Preparation
Text Classification in Tensorflow
The Neuron
How does a model learn?
The Neuron - Section Summary
15 Topics
ANN - Section Introduction
Forward Propagation
The Geometrical Picture
Activation Functions
Multiclass Classification
ANN Code Preparation
Text Classification ANN in Tensorflow
Text Preprocessing Code Preparation
Text Preprocessing in Tensorflow
Embeddings
CBOW (Advanced)
CBOW Exercise Prompt
CBOW in Tensorflow (Advanced)
ANN - Section Summary
Aside: How to Choose Hyperparameters (Optional)
9 Topics
CNN - Section Introduction
What is Convolution?
What is Convolution? (Pattern Matching)
What is Convolution? (Weight Sharing)
Convolution on Color Images
CNN Architecture
CNNs for Text
Convolutional Neural Network for NLP in Tensorflow
CNN - Section Summary
12 Topics
RNN - Section Introduction
Simple RNN / Elman Unit (pt 1)
Simple RNN / Elman Unit (pt 2)
RNN Code Preparation
RNNs: Paying Attention to Shapes
GRU and LSTM (pt 1)
GRU and LSTM (pt 2)
RNN for Text Classification in Tensorflow
Parts-of-Speech (POS) Tagging in Tensorflow
Named Entity Recognition (NER) in Tensorflow
Exercise: Return to CNNs (Advanced)
RNN - Section Summary
3 Topics
Pre-Installation Check
Anaconda Environment Setup
How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow
3 Topics
How to Code by Yourself (part 1)
How to Code by Yourself (part 2)
Proof that using Jupyter Notebook is the same as not using it
4 Topics
How to Succeed in this Course (Long Version)
Is this for Beginners or Experts? Academic or Practical? Fast or slow-paced?
Machine Learning and AI Prerequisite Roadmap (pt 1)
Machine Learning and AI Prerequisite Roadmap (pt 2)
2 Topics
What is the Appendix?
BONUS
Machine Learning: Natural Language Processing in Python (V2)
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