This NLP learning path is tailored for mastering text classification, spanning from data preparation to model optimization. It includes practice in data collection, feature engineering, diverse modeling techniques, and advanced optimization strategies. It aims to develop comprehensive skills in NLP, ensuring learners can construct and refine text classification models efficiently.
This learning path includes:
4 courses with bite-sized lessons and practices
22 engaging lessons in text and video formats
110 hands-on practices in our state-of-the art IDE
One-on-one guidance from Cosmo, our AI tutor
Learn how to collect and prepare specific textual datasets essential for your text classification project. You'll delve into the practices of gathering and cleaning text data, and explore advanced textual processing techniques.
Dive deeper into the transformation of raw text data into features that machine learning models can understand. Through a practical, hands-on approach, you'll learn everything from tokenization, generating Bag-of-Words and TF-IDF representations, to handling sparse features and applying Dimensionality Reduction techniques.
This course paves the way for your journey in NLP modeling. Delve deep into the world of text classification algorithms starting with Naive Bayes, Support Vector Machines, Decision Trees, and Random Forests. But that's not all! You'll also get familiar with stratified cross-validation, a key tool for handling imbalanced classes in text data.
Explore advanced text classification techniques, including ensemble methods and deep learning, to enhance model performance using Python and TensorFlow.
Our built-in AI guide and tutor, Cosmo, prompts you with challenges that are built just for you and unblocks you when you get stuck.
This learning path offers foundational knowledge in Natural Language Processing (NLP). It covers data exploration, preprocessing, text vectorization, and machine learning for text classification. Gain proficiency in transforming text into insights and implementing models to classify text.
Welcome to this extensive learning path designed to transition you from a curious enthusiast to a proficient data science professional. This pathway encompasses a collection of courses tailored to equip learners with the foundational knowledge, tools, and techniques required to unearth actionable insights from raw data. By utilizing Python—one of the most versatile and powerful languages in the data science community—you will be positioned at the forefront of the ever-evolving landscape of data-driven decision-making.
This path will teach you some of the key foundational skills in computer programming often required in technical interviews. It will focus on understanding how to choose optimal algorithms and data structures for different problems, how to apply them, and how to explain their reasoning.