Python Articles

Shingai Manjengwa, the Head of AI Education at Theoriq (ChainML Labs), will discuss the principles of responsible AI and demonstrate how they may be implemented in a world with multiple collaborating agents.

Michelle Conway, Lead Data Scientist at Lloyds Banking Group, will walk you through a simple machine learning example on banking data, including feature engineering, training a model, making predictions, and assessing model performance.

In this session, you'll see a full data workflow using some LIGO gravitational wave data (no physics knowledge required). You'll see how to work with HDF5 files, clean and analyze time series data, and visualize the results.

In this session, you'll learn how to create a simple deep learning model using PyTorch Lightning. You'll work through the steps of defining and training the model, making predictions, and evaluating model performance.

Learn to use MLflow to track and package a machine learning model, and see the process for getting models into production.

In this session you'll learn how to use DataLab to seamlessly access Google Sheets data and analyze the data with Python. Practice with exploratory data analysis tasks like crunching numbers and drawing visualizations for Google Analytics data.

In this introductory session, you'll explore a survey on business innovation. The focus will be on principles of analyzing survey data, and you'll write some simple SQL for calculations and simple Python for data visualizations.

In this webinar, you'll learn how to build your own diffuser model from scratch!

In this webinar, you'll use MLflow to manage a machine learning experiment pipeline. The session will cover model evaluation, hyperparameter tuning, and MLOps strategies, using a London weather dataset.

In this code-along, JP shows you how to use Weaviate, a leading open source vector database, to build apps that can understand and manipulate them based on meaning.

Learn how to manage the features for your machine learning models, to save you time and improve the consistency of your models.

Rewatch this training to discover what synthetic data is, how it protects privacy, and how it's being used to accelerate AI adoption in banking, healthcare, and many other industries.