Technology News - IoT and Machine Learning

Fast Fourier Transform (FFT) is one of the most important algorithms in computer science, electronics and signal processing engineering. It is a fast solver for Discrete Fourier Transform (DFT). Basically, DFT or FFT transforms signals from time-amplitude domain to frequency-amplitude domain. The reverse form of the FFT is known as Inverse Fast Fourier Transform which converts, naturally, signals from frequency domain to time domain. FFT is heavily used in communication, radar or computer systems. For example OFDM (orthogonal frequency division multiplexing) is developed based on IFFT and FFT. Since Python is most common used scientific programming language beside Matlab, I would like to present some information about FFT and using it in Python. This blog post ( https://jakevdp.github.io/blog/2013/08/28/understanding-the-fft/ ) includes the basics of the FFT and very clear comparison of  it to DFT. Another blog post ( https://www.ritchievink.com/blog/2017/04/23/understanding-the-f

I think the first question which must be answered clearly while starting teaching artificial intelligence and machine learning should be about the difference between them. AI - Artificial Intelligence is a comprehensive concept that stating that the computers can learn, think and decide what they should do by themselves in every situation. However, fully AI concept is not possible at the moment as various operations such as image recognition, playing a game, creative thinking etc. require different algorithms which are striving to solve specific problems and tasks. ML - Machine Learning is the specific application of AI, which is mostly relying on learning based on historical data to analyze future data and decide using these analyzes. It can be categorized into supervised and unsupervised learning. Former one utilizes the labelled data to train the machine learning core (brain) and the latter one uses an agent in order to solve the problems. Machine learning algorithms are genera