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    Course content

    About Natural Language Processing Course in Ukraine

  • Where to Get the Code
  • How to Succeed in This Course
  • Temporary 403 Errors

  • 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

  • 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 
  • Language Model (Theory)
  • Language Model (Exercise Prompt)
  • Language Model  
  • Markov Models Section Summary

  • Article Spinning - Problem Description
  • Article Spinning - N-Gram Approach
  • Article Spinner Exercise Prompt
  • Article Spinner in Python  
  • Case Study: Article Spinning Gone Wrong

  • Spam Detection - Problem Description
  • Naive Bayes Intuition
  • Spam Detection - Exercise Prompt
  • Aside: Class Imbalance, ROC, AUC, and F1 Score  
  • Spam Detection in Python

  • 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 

  • 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

  • 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

  • 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

  • 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

  • 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)

  • 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

  • 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
    • Why Should You Learn Natural Language Processing Course in Ukraine Training?

    The annual salary of an Natural Language Processing Course in Ukraine is $125k.

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    What you will get at Zeblearnindia Learning?

    Zeblearnindia Learning is your one-stop institute in Ukraine to learn SAP Online Training Courses, Foreign language, Web Designing, Data Science, Fullstack Developer, Salesforce, Workday, Machine Learning, software testing and video editing. With the flexibility of choosing between online and classroom (offline) modes of learning, our comprehensive courses have been specifically designed for students, working professionals, businessmen and entrepreneurs. Here’s what you’ll get at Zeblearnindia Learning:

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    Track Week Days Course Duration Fast Track
    Week Days 40-45 Days 2 Hrs. Per Day Online
    Course Duration 7 Weekends 3 Hrs. Per Day Online
    Fast Track 8 Days 6+ Hrs. Per Day Online

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    Students Reviews

    Read genuine student reviews on ZebLearn’s expert-led SAP training and foreign language courses. Hear success stories from learners who gained certifications, skills, and career growth!

    Natural Language Processing Course
    Data Scientist
    The Natural Language Processing Course from Zeblearnindia was exceptional. The course provided a thorough understanding of NLP concepts and practical applications. The hands-on projects and detailed explanations of advanced models like BERT and GPT were particularly beneficial. This course has greatly enhanced my ability to work with text data and build NLP solutions.
    Priya Nair
    Machine Learning
    Zeblearnindia’s NLP course was incredibly insightful and well-structured. The modules on text preprocessing and sentiment analysis were especially valuable. The practical exercises and real-world examples helped me grasp complex concepts effectively. I now feel confident in applying NLP techniques to solve problems in my work.
    Ankit Banerjee
    Research Scientist
    I found the Natural Language Processing Course at Zeblearnindia to be highly comprehensive and practical. The in-depth coverage of NLP techniques and the focus on advanced models were extremely useful. The course also provided hands-on experience with NLP projects, which has significantly improved my skills in this field.
    Sneha Patel
    Software Developer
    The NLP course from Zeblearnindia was a fantastic learning experience. The course content was up-to-date and covered everything from basic text preprocessing to advanced NLP models. The instructors were knowledgeable, and the practical applications of NLP concepts were well demonstrated. This course has been invaluable for my career development.
    Rajesh Gupta
    AI Specialist
    Completing the Natural Language Processing Course with Zeblearnindia was a great decision. The course provided a solid foundation in NLP techniques and advanced models. The hands-on projects were particularly helpful in applying what I learned. I now have a deeper understanding of NLP and am better equipped to develop NLP-driven solutions.

    Natural Language Processing Course in Ukraine - Flexible batches for you

    Date Type Schedule Time
    SOLD OUT 14 March 2025 Weekend SAT - SUN (08 Week) 18:00 To 20:00
    Filling Img 19 March 2025 Weekday MON - FRI (08 Week) 08:00 To 10:00
    24 March 2025 Weekend MON - FRI (08 Week) 10:00 To 00:00

    Price  1,20,000

    Now  95,000

    Enroll Now, Pay Later

    Explore Our Courses Across Ukraine - Flexible batches

    We are proud to offer our Natural Language Processing Course in Ukraine services across numerous states of Ukraine.

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