Data Science: Transformers for Natural Language Processing
CTNS
Data Science: Transformers for Natural Language Processing Coupon Code. ChatGPT, GPT-4, BERT, Deep Learning, Machine Learning & NLP with Hugging Face, Attention in Python, Tensorflow, PyTorch
Data Science: Transformers for Natural Language Processing
Data Science: Transformers for Natural Language Processing Course. Ever wondered how AI technologies like OpenAI ChatGPT, GPT-4, Gemini Pro, Llama 3, DALL-E, Midjourney, and Stable Diffusion really work? In this course, you will learn the foundations of these groundbreaking applications. In this course, you will learn very practical skills for applying transformers, and if you want, detailed theory behind how transformers and attention work.
What you’ll learn
- Apply transformers to real-world tasks with just a few lines of code
- Fine-tune transformers on your own datasets with transfer learning
- Sentiment analysis, spam detection, text classification
- NER (named entity recognition), parts-of-speech tagging
- Build your own article spinner for SEO
- Generate believable human-like text
- Neural machine translation and text summarization
- Question-answering (e.g. SQuAD)
- Zero-shot classification
- Understand self-attention and in-depth theory behind transformers
- Implement transformers from scratch
- Use transformers with both Tensorflow and PyTorch
- Understand BERT, GPT, GPT-2, and GPT-3, and where to apply them
- Understand encoder, decoder, and seq2seq architectures
- Master the Hugging Face Python library
- Understand important foundations for OpenAI ChatGPT, GPT-4, DALL-E, Midjourney, and Stable Diffusion
Recommended Course
Math 0-1: Probability for Data Science & Machine Learning Coupon Code
Math 0-1: Probability for Data Science & Machine Learning
Math 0-1: Probability for Data Science & Machine Learning Course. Probability is one of the most important math prerequisites for data science and machine learning. It’s required to understand essentially everything we do, from the latest LLMs like ChatGPT, to diffusion models like Stable Diffusion and Midjourney, to statistics (what I like to call “probability part 2”). Markov chains, an important concept in probability, form the basis of popular models like the Hidden Markov Model (with applications in speech recognition, DNA analysis, and stock trading) and the Markov Decision Process or MDP (the basis for Reinforcement Learning).
Master Time Series Analysis and Forecasting with Python 2025 Coupon Code
Master Time Series Analysis and Forecasting with Python 2025
Master Time Series Analysis and Forecasting with Python 2025 Course. Welcome to the most exciting online course about Forecasting Models in Python. I will show everything you need to know to understand the now and predict the future. Forecasting is always sexy – knowing what will happen usually drops jaws and earns admiration. On top, it is fundamental in the business world. Companies always provide Revenue growth and EBIT estimates, which are based on forecasts. Who is doing them? Well, that could be you!
Who this course is for:
- Anyone who wants to master natural language processing (NLP)
- Anyone who loves deep learning and wants to learn about the most powerful neural network (transformers)
- Anyone who wants to go beyond typical beginner-only courses on Udemy
Instructor
Lazy Programmer Team – The Lazy Programmer is a seasoned online educator with an unwavering passion for sharing knowledge. With over 10 years of experience, he has revolutionized the field of data science and machine learning by captivating audiences worldwide through his comprehensive courses and tutorials.
Equipped with a multidisciplinary background, the Lazy Programmer holds a remarkable duo of master’s degrees. His first foray into academia led him to pursue computer engineering, with a specialized focus on machine learning and pattern recognition. Undeterred by boundaries, he then ventured into the realm of statistics, exploring its applications in financial engineering.
