
Learn Test-Driven Development in Python by implementing Caesar's Cipher. Practice unit testing, follow TDD principles, and participate in a coding challenge to reinforce your new skills.

Explore Jupyter Notebooks for scientific research with Python creators. Learn about its history, benefits, and future in academic publishing and data presentation.

Accelerated introduction to NLP, covering machine learning basics, text preprocessing, vectorization, and advanced neural network architectures like RNNs, LSTMs, and Transformers.

Explore machine learning and computer vision fundamentals, advanced neural network architectures, and applications in object detection and semantic segmentation.

Learn machine learning techniques for tabular data, including model evaluation, feature engineering, tree-based models, hyperparameter tuning, and neural networks using AWS SageMaker.

Explore a lightning talk demonstrating how ZenML, an open-source MLOps framework, facilitates the seamless transition from local development to cloud-scale deployment of generative AI pipelines. Follow a workflow that begins in a Jupyter notebook with lo…

Discover JTaccuino, a new tool for interactive computing tailored specifically for Java developers. Explore how this innovative solution provides a seamless experience for writing Java code and interacting with results through a full graphical interface.…

Explore AI observability tools for ML systems, focusing on logging libraries that enable testing, monitoring, and debugging of AI applications and data pipelines. Learn best practices to enhance MLOps.

Learn to secure AI and ML systems by integrating security into the Machine Learning lifecycle, leveraging DevSecOps principles to create a robust MLSecOps framework.

Dive into hands-on Jupyter Notebooks in Terra with experts from the Broad Institute. Gain practical skills in medical and population genetics data analysis through interactive demonstrations and discussions.

Dive into building and training a custom AI model using PyTorch, Python, and Jupyter Labs. Learn step-by-step techniques to create a deployable model for Raspberry Pi or other computers.

Learn to install and use Jupyter Notebook for data science projects. Covers installation, key features, and a machine learning demo. Ideal for beginners and professionals looking to enhance their coding skills.

Comprehensive introduction to Julia for machine learning, covering installation, basic programming concepts, and data science applications.

Learn Python programming fundamentals through hands-on tutorials covering variables, data types, functions, and data visualization. Ideal for beginners looking to start a career in data science.

Explore scientific computing through Python, covering numerical methods, data analysis, and machine learning, with practical applications in physics and mathematics.

Learn medical statistics using Python and Jupyter notebooks. Covers common tests, data analysis, and visualization techniques. Ideal for healthcare professionals seeking practical skills in statistical analysis.

Comprehensive guide to Python data science tools: Jupyter, Anaconda, Pandas, Scikit-learn, and Matplotlib. Covers data manipulation, model training, and visualization for beginners.

Explore Azure Machine Learning Designer, VS Code ML extension, and PyTorch basics with experts. Demystify ML and NLP concepts while learning about Cognitive Services and AI Playground development.

Learn to secure .NET web apps and APIs using Microsoft Identity Platform, automate Azure AD configurations, and explore new tools for streamlined authentication and authorization in your applications.

Learn to predict music preferences using Python and machine learning. Covers data preparation, model training, accuracy calculation, and decision tree visualization in a hands-on tutorial.

Explore various Python IDEs including Anaconda, Jupyter, PyCharm, and Spyder. Learn their features, benefits, and how to use them effectively for Python programming and development.