Data Science
Showing 901–912 of 1577 results
Introduction to Deep Learning & Neural Networks
The self-contained Deep learning course launched by experienced professional engineers and researchers of the AI Summer team.
Introduction to DevOps principles for machine learning
Get familiar with DevOps principles and tools relevant for MLOps workloads.
Introduction to Graph Machine Learning
This introductory course provides a detailed and lucid explanation of various concepts in Graph Machine Learning, along with coding examples wherever necessary.
Introduction to Hypothesis Testing
Learn how to run t-tests and binomial tests in this introduction to Hypothesis Testing.
Introduction to Hypothesis Testing
Learn how to run t-tests and binomial tests in this introduction to Hypothesis Testing.
Introduction to Importing Data in R
In this course, you will learn to read CSV, XLS, and text files in R using tools like readxl and data.table.
Introduction to Informix Terminology and Data Types (v12.10)
This course introduces students to basic Informix terminology, system access, and data types.
Introduction to JAX and Deep Learning
Introduction to JAX and its ecosystem of libraries.
Introduction to Kubernetes and Red Hat OpenShift Container Platform
This learning offering will explain how does the Red Hat OpenShift Container Platform relate to IBM Cloud Pak for Data.
Introduction to machine learning operations (MLOps)
Machine learning operations (MLOps) applies DevOps principles to machine learning projects. Learn about which DevOps principles help in scaling a machine learning project from experimentation to production.
Introduction to Maps in Folium and Python
Building web map applications like a pro
Introduction to Natural Language Processing with PyTorch
This module explores different neural network architectures for dealing with natural language texts. Natural Language Processing (NLP) is growing in importance due to the ability of language models to accurately "understand" human language faster while using unsupervised training on large text corpora. This module covers different NLP techniques such as using bag-of-words (BoW), word embeddings and recurrent neural networks for classifying text from news headlines to one of the 4 categories (World, Sports, Business, and Sci-Tech).