Learn the basics of Natural Language Processing in Python and build your own Deep Learning Sentiment Analysis!
What you'll learn
Students will be able to install Jupyter Notebook and manage Python Modules
Definition of Natural Language and its Applications
Get to know Basics of Natural Language Processing
Learn Basics of Text Processing with NLTK and spaCy
Get to know Traditional Feature Engineering Models
Implement a working Sentiment Analysis Model
Learn to Code all these points in Python
Requirements
Prior Experience in Python
Prior Implementation of Machine Learning Models will be beneficial
Should have an Interest in Learning Practical Text Mining and Natural Language Processing (NLP)
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FILE LIST
Filename
Size
~Get Your Files Here !/1. Introduction to the Course Jupyter Notebook and Python Modules/1. Install Jupyter Notebook.mp4
28.7 MB
~Get Your Files Here !/1. Introduction to the Course Jupyter Notebook and Python Modules/2. Module Management in Jupyter Notebook.mp4
23.1 MB
~Get Your Files Here !/2. Natural Language Basics/1. Natural Language.mp4
25.4 MB
~Get Your Files Here !/2. Natural Language Basics/2. Natural Language Processing and Applications.mp4
20.6 MB
~Get Your Files Here !/3. Processing Text/1. NLTK and spaCy.mp4
20.2 MB
~Get Your Files Here !/3. Processing Text/2. Tokenization.mp4
9.4 MB
~Get Your Files Here !/3. Processing Text/3. Tokenization in Python.mp4
19.2 MB
~Get Your Files Here !/3. Processing Text/4. Text Cleaning & Case Conversions.mp4
15.3 MB
~Get Your Files Here !/3. Processing Text/5. Text Cleaning & Case Conversions in Python.mp4
36 MB
~Get Your Files Here !/3. Processing Text/6. Stemming & Lemmatization.mp4
20.2 MB
~Get Your Files Here !/3. Processing Text/7. Stemming & Lemmatization in Python.mp4
13.4 MB
~Get Your Files Here !/3. Processing Text/8. Stopwords.mp4
7.2 MB
~Get Your Files Here !/3. Processing Text/9. Stopwords in Python.mp4
21.7 MB
~Get Your Files Here !/4. Traditional Feature Engineering Models/1. Bag of Words Model.mp4
23 MB
~Get Your Files Here !/4. Traditional Feature Engineering Models/2. Bag of N-Grams Model.mp4
15.1 MB
~Get Your Files Here !/4. Traditional Feature Engineering Models/3. Bag of N-Grams Model in Python.mp4
34.5 MB
~Get Your Files Here !/4. Traditional Feature Engineering Models/4. Word2Vec.mp4
19 MB
~Get Your Files Here !/4. Traditional Feature Engineering Models/5. Word2Vec in Python.mp4
25.4 MB
~Get Your Files Here !/4. Traditional Feature Engineering Models/6. BERT Embeddings.mp4
24.6 MB
~Get Your Files Here !/4. Traditional Feature Engineering Models/7. BERT Embeddings in Python.mp4
37.8 MB
~Get Your Files Here !/5. Recap Machine Learning/1. Convolutional Neural Networks for Classification.mp4
27.4 MB
~Get Your Files Here !/6. Text Classification using TensorFlow/1. Python Modules.mp4
16.3 MB
~Get Your Files Here !/6. Text Classification using TensorFlow/2. Dataset.mp4
15.2 MB
~Get Your Files Here !/6. Text Classification using TensorFlow/3. Text Preprocessing.mp4
22.9 MB
~Get Your Files Here !/6. Text Classification using TensorFlow/4. Tokenizing.mp4
9.5 MB
~Get Your Files Here !/6. Text Classification using TensorFlow/5. Preparing Batches.mp4
25.7 MB
~Get Your Files Here !/6. Text Classification using TensorFlow/6. Explaining the Model.mp4
40.1 MB
~Get Your Files Here !/6. Text Classification using TensorFlow/7. Test the Model.mp4