Natural Language Processing (NLP): The Ultimate Course from Beginner to Advanced – Part1
🎥 In this video, we walk step by step through the world of Natural Language Processing (NLP) — from understanding what NLP is, to exploring traditional vs. modern techniques, and finally, hands-on text cleaning and normalization with Python and pandas. By the end, you’ll see how messy travel reviews are transformed into clean, structured data ready for machine learning models.
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🔖 Chapters & Timestamps
00:00:00 1. What is NLP?
00:04:45 2. Traditional vs. Modern NLP Techniques
00:11:00 3. NLP in Action for Businesses
00:15:03 4. Architecture Evolution
00:19:13 5. NLP in the Data Science Workflow
00:23:17 6. Text Preprocessing in NLP
00:27:13 7. Text Cleaning & Normalization in Pandas
00:32:14 8. Full Preprocessing Pipeline Example
00:41:13 9. Conclusion
💻 Code on GitHub: https://github.com/frezazadeh/NLP/blob/main/NLP-Part1.ipynb
⸻
📚 What You’ll Learn
• NLP Basics – How computers make sense of human language.
• Traditional vs. Modern NLP – From TF-IDF and Naïve Bayes to Transformers like BERT and GPT.
• NLP Workflow – How NLP fits into the standard data science pipeline.
• Preprocessing Techniques – Lowercasing, contraction expansion, Unicode normalization, tokenization, stopword removal, lemmatization, and POS tagging.
• Hands-On Demo – Cleaning messy travel reviews with pandas and NLTK.
⸻
✅ Why Watch This Video?
• Step-by-Step Teaching – Complex NLP steps explained in simple terms.
• Practical Python Demo – Full code walkthrough using pandas & NLTK.
• Real-World Example – Travel reviews as the test case for cleaning and modeling text.
• Strong Foundation – Sets you up for more advanced NLP like sentiment analysis, classification, and transformer-based models.
⸻
👍 If this video helped you understand the basics of NLP and preprocessing:
• Like 👍 the video
• Subscribe 🔔 for the next tutorials in this NLP series
• Share ↗ with friends learning data science and AI
💬 Join the Conversation
• Which part of text preprocessing do you find most challenging?
• Do you prefer traditional approaches like TF-IDF, or modern transformers like GPT?
⸻
#NLP #TextPreprocessing #DataScience #MachineLearning #aiexplained
🎥 In this video, we walk step by step through the world of Natural Language Processing (NLP) — from understanding what NLP is, to exploring traditional vs. modern techniques, and finally, hands-on text cleaning and normalization with Python and pandas. By the end, you’ll see how messy travel reviews are transformed into clean, structured data ready for machine learning models.
⸻
🔖 Chapters & Timestamps
00:00:00 1. What is NLP?
00:04:45 2. Traditional vs. Modern NLP Techniques
00:11:00 3. NLP in Action for Businesses
00:15:03 4. Architecture Evolution
00:19:13 5. NLP in the Data Science Workflow
00:23:17 6. Text Preprocessing in NLP
00:27:13 7. Text Cleaning & Normalization in Pandas
00:32:14 8. Full Preprocessing Pipeline Example
00:41:13 9. Conclusion
💻 Code on GitHub: https://github.com/frezazadeh/NLP/blob/main/NLP-Part1.ipynb
⸻
📚 What You’ll Learn
• NLP Basics – How computers make sense of human language.
• Traditional vs. Modern NLP – From TF-IDF and Naïve Bayes to Transformers like BERT and GPT.
• NLP Workflow – How NLP fits into the standard data science pipeline.
• Preprocessing Techniques – Lowercasing, contraction expansion, Unicode normalization, tokenization, stopword removal, lemmatization, and POS tagging.
• Hands-On Demo – Cleaning messy travel reviews with pandas and NLTK.
⸻
✅ Why Watch This Video?
• Step-by-Step Teaching – Complex NLP steps explained in simple terms.
• Practical Python Demo – Full code walkthrough using pandas & NLTK.
• Real-World Example – Travel reviews as the test case for cleaning and modeling text.
• Strong Foundation – Sets you up for more advanced NLP like sentiment analysis, classification, and transformer-based models.
⸻
👍 If this video helped you understand the basics of NLP and preprocessing:
• Like 👍 the video
• Subscribe 🔔 for the next tutorials in this NLP series
• Share ↗ with friends learning data science and AI
💬 Join the Conversation
• Which part of text preprocessing do you find most challenging?
• Do you prefer traditional approaches like TF-IDF, or modern transformers like GPT?
⸻
#NLP #TextPreprocessing #DataScience #MachineLearning #aiexplained
