Monday, February 26, 2024
High-speed and high-performance GPU and CUDA computing! Build Data Science pipelines 50 times faster!
What you'll learn
Understand the differences between processing data using CPU and GPU
Use cuDF as a replacement for pandas for GPU-accelerated processing
Implement codes using cuDF to manipulate DataFrames
Use cuPy as a replacement for numpy for GPU-accelerated processing
Use cuML as a replacement for scikit-learn for GPU-accelerated processing
Implement a complete machine learning project using cuDF and cuML
Compare the performance of classic Python libraries that run on the CPU with RAPIDS libraries that run on the GPU
Implement projects with DASK for parallel and distributed processing
Integrate DASK with cuDF and cuML for GPU performance
Understand the differences between processing data using CPU and GPU
Use cuDF as a replacement for pandas for GPU-accelerated processing
Implement codes using cuDF to manipulate DataFrames
Use cuPy as a replacement for numpy for GPU-accelerated processing
Use cuML as a replacement for scikit-learn for GPU-accelerated processing
Implement a complete machine learning project using cuDF and cuML
Compare the performance of classic Python libraries that run on the CPU with RAPIDS libraries that run on the GPU
Implement projects with DASK for parallel and distributed processing
Integrate DASK with cuDF and cuML for GPU performance