Machine learning Star Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics. ...
Machine learning projects for beginners, final year students, and professionals. The list consists of guided projects, tutorials, and example source code.
If you’re looking to dive into the world of machine learning projects but don’t know where to start, our data pro has curated 12 of the best ML projects.
Explore exciting machine learning projects for beginners. Discover ML project ideas to build skills, from data analysis to predictive modeling.
Continuous growth.Like allartificial intelligence technologies, machine learning is a rapidly evolving field. Projects help you keep up with the latest tools, libraries, as well as identify ML areas in which you need improvement. If you are a newcomer to ML, we recommend you start with the bas...
So here they are: 5 machine learning projects you should definitely have a look at, in no particular order (but numbered like theyarein order, because I like numbering things): 1.Deepy Deepy is an extensible deep learning framework based on Theano. It provides a clean, high-level interface...
Machine Learing Projects All Machine learning,Deep Learning and Computer Vision projects I completed when bored.. List of all Projects Ageing Face similarities Groups faces based on similar aged faces. Animal Intrusion Alarm Detects animal in video stream and send alert Email Human Behaviour Detect ...
Machine Learning Projects: 1. Enron Email Dataset The Enron Dataset is popular in natural language processing. It has more than 500K emails of over 150 users. The size of the data is around 432Mb. Out of 150 users, most of the users are the senior management of Enron. ...
Learn what machine learning is, how it differs from AI and deep learning, and why it is one of the most exciting fields in data science.
The use of algorithms and model training in machine learning was introduced in the 1950s. Applications at the time were minor. However, fundamental concepts that established the logic behind ML were proposed by a number of pioneering mathematicians and scientists, e.g., Alan Turing; Allen Newell...