Matrix decomposition in linear algebra is one of the most valuable techniques for reducing the matrix into smaller parts. In matrix decomposition, the eigendecomposition is a fundamental concept that decomposes the matrix in eigen values and eigen vectors. This type of decomposition technique plays an essential role in techniques like Principle component analysis where there …
Data and its quality affect machine learning models and their accuracy, and the quality of the data can not be well in some types of problems which can be solved by machine learning. Here the scale of the data is also represented as the quality of the data, which needs to be expected while training …
Cost functions in machine learning measure the performance of the machine learning algorithm trained on a particular dataset. By measuring the cost function or cost for a specific model, we can easily measure the error of the machine-learning model trained. There are many types of cost functions, from which depending on the problem statement the …
10 Classification Cost Functions in Machine Learning Read More »
Machine learning is the concept that a computer program can learn and adapt to new data without human intervention. It is a sub-field of artificial intelligence that keeps a computer’s built-in algorithms current regardless of changes in the worldwide economy. Currently, most companies and agencies are using machine-learning techniques to solve their business problem, these …
How to Frame a Machine Learning Problem | Design Your Data Science Project Read More »
The Ensemble technique is one of the best-performing techniques used in the field of machine learning for getting better results on complex types of datasets. There are many ensemble techniques available that use multiple machine-learning algorithms for training on the same dataset and return great results compared to the single normal machine-learning algorithms. In this …
Statistics is a critical component of data science and machine learning algorithms. Almost all the machine learning algorithms use mathematics in the backend, which is linear algebra and statistics. Learning and understanding the core intuition and the working mechanisms of any machine learning algorithm requires a core knowledge of statistics. In this article, we will …
