/Machine Learning Fundamentals 2024-10-16T16:42:30+02:00 Ahmet Taspinar / Jekyll © 2024 Ahmet Taspinar /assets/img/favicons/favicon.ico /assets/img/favicons/favicon-96x96.png An introduction to solving differential equations numerically2022-04-05T00:00:00+02:00 2024-10-16T16:37:00+02:00 /posts/an-introduction-to-solving-differential-equations-numerically/ ataspinar In this blog-post we will have a look at how Differential Equations (DE) can be solved numerically via the Finite Differences method. By solving differential equations we can run simulations of dynamical systems and make predictions about the world. The reason for writing this blog-post is because I am interested in a new type of Neural Networks called Physics Informed Neural Networks (PINN). ... Time-Series forecasting with Stochastic Signal Analysis techniques2020-12-21T23:00:00+01:00 2024-10-16T16:37:00+02:00 /posts/time-series-forecasting-with-stochastic-signal-analysis-techniques/ ataspinar 1. Introduction In other blog-posts we have seen how we can use Stochastic signal analysis techniques for the classification of time-series and signals, and also how we can use the Wavelet Transform for classification and other Machine Learning related tasks. This blog-post can be seen as an introduction to those blog-posts and explains some of the more fundamental concepts regarding the Four... A guide for using the Wavelet Transform in Machine Learning2018-12-20T23:00:00+01:00 2024-10-16T16:37:00+02:00 /posts/a-guide-for-using-the-wavelet-transform-in-machine-learning/ ataspinar 1. Introduction In a previous blog-post we have seen how we can use Signal Processing techniques for the classification of time-series and signals. A very short summary of that post is: We can use the Fourier Transform to transform a signal from its time-domain to its frequency domain. The peaks in the frequency spectrum indicate the most occurring frequencies in the signal. The larger and s... Building Recurrent Neural Networks in Tensorflow2018-07-05T00:00:00+02:00 2024-10-16T16:35:11+02:00 /posts/building-recurrent-neural-networks-in-tensorflow/ ataspinar In the previous blog posts we have seen how we can build Convolutional Neural Networks in Tensorflow and also how we can use Stochastic Signal Analysis techniques to classify signals and time-series. In this blog post, lets have a look and see how we can build Recurrent Neural Networks in Tensorflow and use them to classify Signals. 1. Introduction to Recurrent Neural Networks Recurrent Neura... Machine Learning with Signal Processing Techniques2018-04-04T00:00:00+02:00 2024-10-16T16:35:11+02:00 /posts/machine-learning-with-signal-processing-techniques/ ataspinar Stochastic Signal Analysis is a field of science concerned with the processing, modification and analysis of (stochastic) signals. Anyone with a background in Physics or Engineering knows to some degree about signal analysis techniques, what these technique are and how they can be used to analyze, model and classify signals. Data Scientists coming from a different fields, like Computer Scienc...