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Introduction to Python and Machine Learning Workshops

Welcome to the Introduction to Python and Machine Learning Workshops! These workshops are designed for developers who want to learn about machine learning and deep learning, and how to integrate them into their applications. Whether you're new to machine learning or have some experience with the tools, these workshops will provide you with the knowledge and skills you need to build and deploy machine learning models using OpenVINO.

This workshop series is sponsored by Intel and we will be using OpenVINO throughout the series, which is a toolkit for optimizing deep learning models for different hardware architectures. Throughout the workshops, you'll learn about the different types of tasks that deep learning can be used for, including classification, detection, and segmentation. You'll also learn how to build and optimize deep learning models using popular tools like TensorFlow and PyTorch, and how to deploy those models using OpenVINO. By the end of the series, you'll be able to build and deploy a deep learning model optimized for a specific task.

Workshop 1: Introduction to Python, Deep Learning and OpenVINO

• Introduction to deep learning and its applications.
• Why Python is a popular language for machine learning and deep learning, and an overview of popular libraries and frameworks, including TensorFlow, PyTorch, and OpenCV.
• Overview of Docker and its advantages for development environments.
• Explaining the different types of tasks that deep learning can be used for (classification, detection, segmentation, etc.).
• An overview of OpenVINO and how it can help optimize deep learning models for different hardware architectures.

Workshop 2: Data Preparation and Model Training

• The importance of data preparation and cleaning.
• How to load and preprocess data for deep learning tasks.
• Data visualization and exploration.
• Exploring the basics of model training, including loss functions and optimization algorithms.
• Building a simple neural network for image classification using TensorFlow or PyTorch.
• Training the model on a dataset and evaluate its performance.

Workshop 3: Building Classification Models with OpenVINO

• Introduction to image classification and its applications.
• Building a simple image classification model using a pre-trained model.
• Converting the model to the OpenVINO format and optimize it for different hardware architectures.
• Deploying the optimized model and measure its performance.

Workshop 4: Building Object Detection Models with OpenVINO

• Introduction to object detection and its applications.
• Building a simple object detection model using a pre-trained model.
• Converting the model to the OpenVINO format and optimize it for different hardware architectures.
• Deploying the optimized model and measuring its performance.

Thanks to Intel

These sessions are sponsored by Intel. Take a look at this post about How to put your Python skills to work.

You will learn about the Edge AI Certification and the 30-Day AI Dev Challenge.

Consider joining the challenge!