Enroll Course: https://www.udemy.com/course/natural-language-processing-in-python/
Have you ever marveled at the capabilities of AI like ChatGPT, GPT-4, DALL-E, or Midjourney? Ever wondered what makes them tick? The ‘Machine Learning: Natural Language Processing in Python (V2)’ course on Udemy is your gateway to understanding the foundational principles behind these groundbreaking technologies.
This comprehensive course is structured as a massive 4-in-1 program, meticulously covering the essential aspects of Natural Language Processing (NLP). It begins with the fundamental concepts of vector models and text preprocessing, explaining why vectors are crucial in AI and data science. You’ll get hands-on with techniques like CountVectorizer and TF-IDF, and even delve into neural embedding methods such as word2vec and GloVe. The practical applications are extensive, including text classification, document retrieval, and text summarization. Crucially, you’ll master essential preprocessing steps like tokenization, stemming, and lemmatization, and even get a glimpse into classic NLP tasks like part-of-speech tagging.
The second part of the course shifts focus to probability models and Markov models, highlighting their 100-year legacy and diverse applications beyond NLP, from finance to bioinformatics. You’ll learn how these models are used to build text classifiers, generate creative content like poetry, and crucially, serve as a vital prerequisite for understanding modern Transformer models like BERT and GPT-3, including their pre-training objectives.
Part three dives into machine learning methods, focusing on practical applications for classic NLP tasks such as spam detection, sentiment analysis, latent semantic analysis, and topic modeling. While theory is included, the emphasis is on application, using algorithms like Naive Bayes, Logistic Regression, PCA/SVD, and LDA – all staples in the NLP field.
Finally, the course culminates in deep learning methods, exploring modern neural network architectures like Feedforward ANNs, Embeddings, CNNs, and RNNs (including LSTMs and GRUs). These are the very architectures powering advanced applications like language translation and speech recognition, and understanding them is key to grasping the complexity of Transformers.
What truly sets this course apart is its commitment to clarity and depth. Every line of code is explained, ensuring you understand the ‘why’ behind the ‘how’. Unlike other courses that rush through coding, this one prioritizes genuine learning. It doesn’t shy away from university-level mathematics, providing the detailed algorithmic insights that are often omitted elsewhere. If you’re serious about understanding the core of modern AI and NLP, this course is an invaluable investment.
Enroll Course: https://www.udemy.com/course/natural-language-processing-in-python/