In this article, you will learn about conditional GAN (Generative Adversarial Network) and will be able to build one from scratch. After that you will be able to apply the cGAN model on a fashion products dataset for converting sketches of products to color images. If you would like to understand what are GANs [1] you can check out our previous tutorials on Latent Spaces. If we would like to generate one set of images while giving a different set of images as an input to a GAN model, this problem is called Image Translation. A classic GAN architecture doesn't take into account class labels therefore, we require a modified version of GAN.

Azure, combined with Microsoft Cognitive Services, are a huge opportunity for developers. Has Microsoft's Cognitive services piqued your interest, but you haven't been able to find a decent course that will teach you how to use those services effectively? Or maybe you have just recognised how a valuable skill like machine learning can open up big opportunities for you as a developer. Perhaps you just wanted to find out how to add "superpowers" to your programs to do amazing things like face detection, but had no idea how to go about it. Whatever the reason that has brought you to this page, one thing is for sure; the information you are looking for is contained in this course!

Machine Learning is a hot topic! Machine Learning is a hot topic! Python Developers who understand how to work with Machine Learning are in high demand. But how do you get started? Maybe you tried to get started with Machine Learning, but couldn't find decent tutorials online to bring you up to speed, fast.

From sifting through Twitter data to making your own Minecraft modifications, Python is one of the most versatile programming languages at a coder's disposal. The open-source, object-oriented language is also quickly becoming one of the most-used languages in data science. According to the Association for Computing Machinery, Python is now the most popular introductory language at universities in the United States. To help readers practice the Python fundamentals, datascience@berkeley gathered six coding problems, including some from the W200: Introduction to Data Science Programming course. Consider the following questions to make sure you have the proper prior knowledge and coding environment to continue.

Convert image to editable excel. "Level Up" for Beginners who are interested in Big Data and Machine Learning (using Python). This Step-by-Step Course is intended to be an initiation to learn #BigData and #MachineLearning with #Python programming for absolute beginners that have no background in programming. In this course, we will step by step, using the example of real data, we will go through the main processes related to the topic "Big data and machine learning". Since the material turned out to be voluminous, I divided the course into five parts.

This course is intended to be an initiation to learn #BigData and #MachineLearning & #AI with #Python programming for absolute beginners that have no background in programming. In this course, we will step by step, using the example of real data, we will go through the main processes related to the topic "Big data and machine learning". Since the material turned out to be voluminous, I divided the course into five parts. We will examine in detail the basic types, terms and algorithms of machine learning. We go through the basic concepts of machine learning that beginners need.

Abalone is a common name for any of a group of small to very large sea snails, marine gastropod molluscs in the family Haliotidae. Other common names are ear shells, sea ears, and muttonfish or muttonshells in Australia, ormer in the UK, perlemoen in South Africa, and paua in New Zealand. The age of abalone is determined by cutting the shell through the cone, staining it, and counting the number of rings through a microscope a boring and time consuming task. Other measurements, which are easier to obtain, are used to predict the age. Given is the attribute name, attribute type, the measurement unit and a brief description.

Python was slowly becoming the de-facto language for Deep Learning models. In this course you will learn how to build powerful convolutional neural networks in R, from scratch. This special kind of deep networks is used to make accurate predictions in various fields of research, either academic or practical. If you want to use R for advanced tasks like image recognition, face detection or handwriting recognition, this course is the best place to start. All the procedures are explained live, step by step, in every detail. Most important, you will be able to apply immediately what you will learn, by simply replicating and adapting the code we will be using in the course.

They are powerful data mining techniques that allow you to detect patterns in your data or variables. For each technique, a number of practical exercises are proposed. By doing these exercises you'll actually apply in practice what you have learned. This course is your opportunity to become a machine learning expert in a few weeks only! With my video lectures, you will find it very easy to master the major machine learning techniques. Everything is shown live, step by step, so you can replicate any procedure at any time you need it. So click the "Enroll" button to get instant access to your machine learning course. It will surely provide you with new priceless skills. And, who knows, it could give you a tremendous career boost in the near future.

Prepare your drone flight, analyze the resulting data, and prepare professional reports using QGIS. GIS and Drone Technologies are both powerful tools for assisting people in analyzing the world we inhabit. Whether you are someone with GIS skills looking to add drones to your toolbelt, or a drone pilot who wants to level up their deliverable products, you are in the right place. Both these skills require very similar mindsets, such as an attention to detail, focus and accuracy. If you can do one, you can do the other, so why not do both!