Artificial intelligence is a modern societies feature. You might have heard about Magenta or Deep dreams, AI which manages to create artworks such as pictures, sketches or music files from scratch. Well not exactly from scratch but after analyzing terabytes of the real composers’ notes, artists pictures and numbers. What is important about Magenta and Deep dreams is that by using the algorithms and logical connections AI becomes able to create another program or physical object, it can learn and, probably think. In this article, we shall have a look at some machine learning projects that you can try out
Machine learning can be called an application of AI based on the idea that we should really just be able to give machines access to data and let them learn for themselves.
Some call Machine learning models black boxes, as they receive tons of data and provide the user with a very accurate answer, usually without any explanation. Despite all concerns, the machine learning by itself becomes more and more popular.
Machine learning is a discipline that began in the 18th century as part of the theory of statistics. But today it is relevant as never before.
Machine learning is a process in which the system processes a large number of examples, identifies patterns and uses them to predict the characteristics of new data. Amazon, eBay most relevant to your product offers, youtube recommendations all of this programs are based on Machine learning when a program analyses your last shopping history or your youtube video search and based on your preferences sends you the new offers. However, these examples are too boring and very used to, so I have collected 10 most outstanding Machine learning projects which were created by the 2018 year.
Library of words and text classification, created by Facebook Research. A very useful tool on web and application search, spam filtering, content ranking also in targeted marketing and sentiment analysis. The project is a mix of the most prosperous approaches of natural language processing and machine learning teams in the last 10 years.
2.Deep Photo style transfer.
Program for rendering photos with transferring styles using neural networks. Creator – Fujun Luan, a professor at Cornell University. Project very similar to deep dreams, when Machine takes your picture and applies different drawing styles such as cubism, surrealism and etc.
The easiest face recognition API for Python. Creator –Adam Gategay.
Project Magenta was launched in 2016 and now is known for generating its own musical compositions, images, drawings, and other materials. The most recent Magenta project is music composition, inspired by Beatles in collaboration with Sony, the composition’s name is simple: “Daddy’s car”
Library for the Machine Learning, which works in the browser. Creator – Nikhil Torat from Google Brain. A part of the TensorFlow.js ecosystem, this repo hosts @tensorflow/tfjs-core, the TensorFlow.js Core API, which provides low-level, hardware-accelerated linear algebra operations and an eager API for automatic differentiation. Deeplearn.js is an GPU license based open-source library which allows to train neural networks in a browser (Only Google Chrome initially )or run pre-trained models in inference mode.
It is a Python component of a DeepMinds’ of the strategic online game StarCraft II learning environment, abbreviation(SC2LE), which provides an interface for RL agents to interact with the game, get observations and send actions.
Image-to-image image transformation, created Jun-Yan Zhu a professor at the University of California at Berkeley and Taesung Park, in collaboration with Tongzhou Wang. PyTorch Image is able to transform horses into zebras, Monet paintings – in photography, the summer landscape – in winter, etc.
This is a simulator for drones, cars and more, built on Unreal Engine. As well as all here mentioned machine learning projects, this is an open-source cross-platform, which provides the user with physically and visually realistic simulations. Developed as an Unreal plugin, Airsim is used to test how safely autonomously operated vehicles, which use AI, can operate in a real world without danger for people and their property.
Abbreviated as T2T, it is a deep learning model’ and datasets library, created to make deep learning more accessible to accelerate Machine learning research .T2T is actively used and maintained by researchers and engineers within the Google Brain team and a community of users.
A dataset of Zalando’s article images—consisting of a training set of 60,000 examples and a test set of 10,000 examples.
All mentioned machine learning projects are just a drop of water in the ocean of digital technologies. Every year this list is supplemented by new discoveries. Companies are constantly improving their services to increase sales, provide the customer with quick and effective assistance, make more accurate predictions and perform those tasks that do not cause difficulties in humans. Machine learning is become extremely helpful in such a quest, first of all, that the internet is a virtually inexhaustible source of data needed and the human brain is an inexhaustible source of ideas how to incorporate this data.