MACHINE LEARNING

Someone once thought about what if computers were able to learn independently and progress without any human programming or help from experience using data. This theory came to be known as Machine Learning, and the name behind was Arthur Samuel. Thanks to the substantial volume of data available…

Machine learning has been one of the world’s hottest subjects in the last decade, and Andrew Ng a machine learning expert treats it as the latest electricity. Many of the services we use today’s global machine learning powers-recommendation systems such as Netflix, YouTube, and Spotify;…

Deep learning has revolutionized computer vision over the past decade. Several vision tasks such as object recognition, semantic segmentation, optical flow estimation, and more can now be resolved with unparalleled precision using deep neural networks. Breakthroughs in deep learning have led to…

AutoML provides tools that automatically discover good machine learning model pipelines for a particular dataset without much user intervention. It is ideal for machine learning practitioners or domain experts new to machine learning to get quick and good results for a predictive modeling task.…

In machine learning, reducing dimensionality is a critical approach. Overfitting of the learning model may result in a large number of features available in the dataset. There are two standard dimensionality reduction techniques used by machine learning experts to evaluate the collection of…

Decision trees are part of the Supervised Classification Algorithm family. On classification issues, they work very well, the decisional route is reasonably easy to understand, and the algorithm is fast and straightforward. Random Forest is the ensemble variant of Decision Trees. Random forest is a…

Machine learning is nothing but a research field that allows computers without any specific programming to “learn” like humans. High-dimensionality statistics and dimensionality reduction techniques that have been used for data visualization. These techniques are applied in machine…

Naïve Bayes is a surprisingly powerful yet simple algorithm for predictive modeling. It is a machine learning model that can handle large volumes of data, including millions of data records. Naïve Bayes is the recommended approach for Natural Language Processing tasks such as sentiment analysis as…

Machine learning is a scientific technique where computers learn how to solve a problem without directly programming them. The ML race is currently led by deep learning fuelled by improved algorithms, computing power and big data. The classical algorithms of ML still have a firm place in the field.…

In machine learning, there is much discussion around tensors being the cornerstone data structure. Tensor is a type of data structure used in linear algebra that can be used for arithmetic operations like matrices and vectors. In 2015, researchers at Google came up with TensorFlow, which is now…

If a CPU is a PC’s core, then the soul is a GPU. While most PCs can run without a good GPU, without one, neural networking is not possible. Machine learning experts suggest that complex operations like matrix manipulation, exceptional computational prerequisites, and significant computing…

IPFS, even among many in the Valley, is not exactly a well-known technology yet, but it is spreading quickly by word of mouth among people in the open-source community. Many are thrilled by its ability to boost file transfer and streaming speeds across the Internet significantly. In a way that is…