Data Science
Showing 709–720 of 1255 results
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).
Introduction to natural language processing with TensorFlow
In this module, we'll explore different neural network architectures for processing natural language texts. Natural Language Processing (NLP) has experienced fast growth and advancement primarily because the performance of the language models depends on their overall ability to "understand" text and can be trained using an unsupervised technique on large text corpora. Additionally, pre-trained text models (such as BERT) simplified many NLP tasks and has dramatically improved the performance. We'll learn more about these techniques and the basics of NLP in this learning module.
Introduction to Network Analysis in Python
This course will equip you with the skills to analyze, visualize, and make sense of networks using the NetworkX library.
Introduction to NumPy
Master your skills in NumPy by learning how to create, sort, filter, and update arrays using NYC’s tree census.
Introduction to Optimization in Python
Learn to solve real-world optimization problems using Python's SciPy and PuLP, covering everything from basic to constrained and complex optimization.
Introduction to Predictive Analytics in Python
In this course you'll learn to use and present logistic regression models for making predictions.