Welcome to this course "Complete Machine Learning Masterclass – Learn From Scratch". In this course you will learn from scratch. We will assume that you are a complete beginner and by the end of the course you will be at advanced level. This course contain Real-World examples and Hands On practicals. We will guide you step by step so that you can understand better.
Enver Yucel is the founder of BAU Global, a broad education network headquartered in Turkey, consisting of five universities, three language schools, four academic centers and one boarding school spread across North America, Europe, Africa and Asia. Yucel has devoted his life to education, having served an estimated 150,000 students since starting his first institution with three class rooms in Istanbul in 1974. He is also a member of the Advisory Board of the UN Institute for Training and Research. He was invited to speak at the AI World Conference & Expo in Boston in the fall of 2019, the first Turkish speaker in the four years of the conference. He recently took some time to answer questions posed by AI Trends Editor John P Desmond, who was in the audience for his Boston talk.
In my previous post I talked about using a portable EEG device to detect Event Related Potentials (ERP's) in the brain. Specifically, I was able to detect a Reward Positivity (RewP) signal after a puzzle was solved correctly. I did this by graphing the signal immediately after the event and comparing it with the average RewP signal from this paper. Using my human brain's visual pattern recognition, I confirmed that I was getting the same pattern. Wouldn't it be interesting to train a machine learning model to recognize the same pattern so we can monitor these events automatically.
AI4ALL Open Learning is a free program which community-based organisations, as well as teachers, can use the resource to educate the community and high-school students about Artificial Intelligence. Recently, AI4ALL announced a new module which high school teachers with a free online lesson to engage students around AI's role in the current crisis. In the program, the ExploreAI curriculum can be implemented in 10, 20 or 30 hrs. The reason behind this program is to support the community by sharing relevant, free curriculum and teaching resources. AI4All is trying every possible way to ensure the best to serve all people in the work to increase diversity and inclusion in artificial intelligence.
For building any machine learning model, it is important to have a sufficient amount of data to train the model. The data is often collected from various resources and might be available in different formats. Due to this reason, data cleaning and preprocessing become a crucial step in the machine learning project. Whenever new data points are added to the existing data, we need to perform the same preprocessing steps again before we can use the machine learning model to make predictions. This becomes a tedious and time-consuming process!
McMarvin Research has been exploring artificial intelligence and machine learning technologies and techniques for decades. We believe AI will transform the world in dramatic ways in the coming years – and we're advancing the field through our portfolio of research focused on three areas: Advancing AI, Scaling AI, and Trusting AI. We're also working to accelerate AI research through collaboration with like-minded institutions and individuals to push the boundaries of AI faster – for the benefit of industry and society. It's a living, changing entity that powers change throughout every industry across the globe. As it evolves, so do we all.
By Clare Liu, Data Scientist at fintech industry, based in HK. One of the most prevailing and exciting supervised learning models with associated learning algorithms that analyse data and recognise patterns is Support Vector Machines (SVMs). It is used for solving both regression and classification problems. However, it is mostly used in solving classification problems. SVMs were first introduced by B.E. Boser et al. in 1992 and has become popular due to success in handwritten digit recognition in 1994.
Today machines with artificial intelligence (AI) are becoming more prevalent in society. Across many fields, AI has taken over numerous tasks that humans used to do earlier. As the reference is to human intelligence, artificial intelligence is being modified into what humans can do. However, the technology has not yet matched the level of utmost wisdom possessed by humans and it seems like it is not going to achieve the milestone any time sooner. To replace human beings at most jobs, machines need to exhibit what we intuitively call "common sense".