Articles About Machine Learning

Very Deep Neural Networks Explained in 40 Seconds

By Vincent Granville, Ph.D., Author at MLtechniques.com Sponsored Post Very deep neural networks (VDNN) illustrated with data animation: a 40 second video, featuring supervised learning, layers, neurons, fuzzy classification, and convolution filters. It is said that a picture is worth a thousand words. Here instead, I use a video to illustrate the concept of very deep neural networks (VDNN). I use a supervised classification problem to explain how a VDNN works. Supervised classification is one of the main algorithms in supervised […]

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Massaging Data Using Pandas

When we talk about managing data, it is quite inevitable to see data presented in tables. With column header, and sometimes with names for rows, it makes understanding data easier. In fact, it often happens that we see data of different types staying together. For example, we have quantity as numbers and name as strings in a table of ingredients for a recipe. In Python, we have the pandas library to help us handle tabular data. After finishing this tutorial, […]

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Web Crawling in Python

In the old days, it was a tedious job to collect data, and it was sometimes very expensive. Machine learning projects cannot live without data. Luckily, we have a lot of data on the web at our disposal nowadays. We can copy data from the web to create our dataset. We can manually download files and save them to the disk. But we can do it more efficiently by automating the data harvesting. There are several tools in Python that […]

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Managing Data for Machine Learning Projects

Big data, labeled data, noisy data. Machine learning projects all need to look at data. Data is a critical aspect of machine learning projects, and how we handle that data is an important consideration for our project. When the amount of data grows, and there is a need to manage them, allow them to serve multiple projects, or simply have a better way to retrieve data, it is natural to consider using a database system. It can be a relational […]

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A First Course on Deploying Python Projects

After all the hard work developing a project in Python, we want to share our project with other people. It can be your friends or your colleagues. Maybe they are not interested in your code, but they want to run it and make some real use of it. For example, you create a regression model that can predict a value based on input features. Your friend wants to provide their own feature and see what value your model predicts. But […]

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Web Frameworks for Your Python Projects

When we finish a Python project and roll it out for other people to use, the easiest way is to present our project as a command-line program. If you want to make it friendlier, you may want to develop a GUI for your program so people can interact with it with mouse clicks while it runs. Developing a GUI can be difficult as the model of human-computer interaction is complex. Therefore, a compromise is to create a web interface for […]

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Using OpenPose with Stable Diffusion

We have just learned about ControlNet. Now, let’s explore the most effective way to control your character based on human pose. OpenPose is a great tool that can detect body keypoint locations in images and video. By integrating OpenPose with Stable Diffusion, we can guide the AI in generating images that match specific poses. In this post, you will learn about ControlNet’s OpenPose and how to use it to generate similar pose characters. Specifically, we will cover: What is Openpose, […]

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More Prompting Techniques for Stable Diffusion

The image diffusion model, in its simplest form, generates an image from the prompt. The prompt can be a text prompt or an image as long as a suitable encoder is available to convert it into a tensor that the model can use as a condition to guide the generation process. Text prompts are probably the easiest way to provide conditioning. It is easy to provide, but you may not find it easy enough to generate a picture that matches […]

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Using ControlNet with Stable Diffusion

ControlNet is a neural network that can improve image generation in Stable Diffusion by adding extra conditions. This allows users to have more control over the images generated. Instead of trying out different prompts, the ControlNet models enable users to generate consistent images with just one prompt. In this post, you will learn how to gain precise control over images generated by Stable Diffusion using ControlNet. Specifically, we will cover: What is ControlNet, and how it works How to use […]

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Inpainting and Outpainting with Stable Diffusion

Inpainting and outpainting have long been popular and well-studied image processing domains. Traditional approaches to these problems often relied on complex algorithms and deep learning techniques yet still gave inconsistent outputs. However, recent advancements in the form of Stable diffusion have reshaped these domains. Stable diffusion now offers enhanced efficacy in inpainting and outpainting while maintaining a remarkably lightweight nature. In this post, you will explore the concepts of inpainting and outpainting and see how you can do these with […]

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