Machine Learning
Showing 37–48 of 273 results
Building, Training, and Validating Models in Microsoft Azure
This course gives Microsoft Azure Data Scientists a road map on how to build, train, and validate machine learning models in Azure.
CI/CD for Machine Learning
Elevate your Machine Learning Development with CI/CD using GitHub Actions and Data Version Control
Continuous Model Training with Evolving Data Streams
Are you facing the challenge of ever-changing data when it comes to machine learning? This course will teach you how to continuously train and adapt your models, ensuring long-term effectiveness.
Convolutional Neural Networks (CNNs): Visual Mastery with Deep Learning
Dive into the world of deep learning with CNNs using TensorFlow and Keras. This course will teach you how to build and optimize CNN models for real-world applications.
Create confusion matrices and compute metrics with Python
Understand how to create confusion matrices and compute essential model metrics in Python. Learn to evaluate classification models with metrics like accuracy, precision, recall, F1-score, and ROC-AUC to gauge their performance.
Creating & Deploying Microsoft Azure Machine Learning Studio Solutions
This course will provide an introduction to the power, flexibility and scalability of Azure Machine Learning. You will learn to implement the data science process, to prepare data and integrate data sources for use in machine learning experiments.
Creating a Content-Based Recommendation System
Learn how to create a content-based recommendation system. Understand how to leverage user preferences, item features, and machine learning algorithms to build personalized recommendation engines for e-commerce, media, and more.
Creating anime characters using DCGANs and Keras
Dive into the world of deep learning by creating anime characters using DCGANs (Deep Convolutional Generative Adversarial Networks) and Keras. Learn how to train GANs to generate stunning and realistic anime-style artwork from scratch.
Credit Risk Modeling in Python
Learn how to prepare credit application data, apply machine learning and business rules to reduce risk and ensure profitability.
Customer Clustering with KMeans to Boost Business Strategy
Learn how to apply the KMeans clustering algorithm to segment customers and enhance business strategies. Discover how to identify patterns, optimize marketing efforts, and drive targeted decisions using unsupervised learning techniques.
Data and Programming Foundations for AI
Learn the coding, data science, and math you need to get started as a Machine Learning or AI engineer.
Data classification with Naive Bayes
Master data classification using Naive Bayes, a simple yet powerful probabilistic algorithm. Learn how to apply it to various datasets for tasks like spam detection, sentiment analysis, and classification of categorical data.