“…A solid understanding of C++ and basic linear algebra, as well as experience in creating custom 3D applications without using premade rendering engines is required…”

“…Skill Level Intermediate Advanced Learn How To Recognize which type of transformer-based model is best for a given task Understand how transformers process text and make predictions Fine-tune a transformer-based model Create pipelines using fine-tuned models Deploy fine-tuned models and use them in production Who Should Take This Course Intermediate/advanced machine learning engineers with experience with ML, neural networks, and NLP Those interested in state-of-the art NLP architecture Those interested in productionizing NLP models Those comfortable using libraries like Tensorflow or PyTorch Those comfortable with linear algebra and vector/matrix operations Course Requirements Python 3 proficiency with some experience working in interactive Python environments including Notebooks (Jupyter/Google Colab/Kaggle Kernels) Comfortable using the Pandas library and either Tensorflow or PyTorch Understanding of ML/deep learning fundamentals including train/test splits, loss/cost functions, and gradient descent About Pearson Video Training: Pearson publishes expert-led video tutorials covering a wide selection of technology topics designed to teach you the skills you need to succeed. …”

“…There's no heavy theory, and you'll learn how to offload most equations to the SymPy computer algebra system. What's Inside Speak the language of applied geometry Compose geometric transformations economically Craft custom splines for efficient curves and surface generation Confidently use geometry algorithms About the Reader Examples are in Python, and all you need is high school-level math. …”

“…One must have decent Python programming skills and a basic understanding of linear algebra and probability for this course. About The Author Lazy Programmer: The Lazy Programmer is an AI and machine learning engineer with a focus on deep learning, who also has experience in data science, big data engineering, and full-stack software engineering. …”