An Introduction to Machine Learning & NLP in Python
Learn fundamental natural language processing techniques using Python and how to apply them to extract insights from real-world text data.
Tailored for beginners and Python enthusiasts, this program provides a comprehensive foundation in two powerful domains—Machine Learning and Natural Language Processing—ushering learners into the exciting world of data-driven insights and language understanding.
What You Will Learn:
- Introduction to Machine Learning:
- Gain a fundamental understanding of the core concepts of machine learning.
- Explore supervised and unsupervised learning, as well as key algorithms for classification and regression.
- NLP Fundamentals:
- Dive into the foundations of Natural Language Processing.
- Understand the challenges and opportunities in processing and analyzing human language.
- Data Preprocessing for ML & NLP:
- Learn essential techniques for preparing and cleaning data for machine learning and NLP tasks.
- Explore text preprocessing methods, handling missing data, and transforming raw data into a usable format.
- Text Representation Techniques:
- Understand various techniques for representing text data, including bag-of-words, TF-IDF, and word embeddings.
- Explore how these techniques capture the semantic meaning of words and documents.
- Supervised Learning for Text Classification:
- Apply machine learning algorithms to solve text classification problems.
- Learn how to build models that can categorize and classify text data into predefined categories.
- Unsupervised Learning for Text Clustering:
- Explore unsupervised learning techniques for clustering similar text documents.
- Understand how clustering algorithms group together documents with similar themes or topics.
- NLP Applications and Real-World Projects:
- Apply your knowledge through hands-on projects, solving real-world problems in both machine learning and NLP.
- Gain practical experience in building and deploying models for text analysis.
This course is an excellent starting point for anyone interested in these fascinating fields. The instructors provide clear explanations and practical examples that make complex concepts accessible, even for beginners.
— Anna
The machine learning and NLP concepts were introduced gradually, and the practical examples helped solidify my understanding. The balance between theory and application was just right, and I found the real-world projects to be particularly insightful.
— Jake
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