Do you want to know what is linear regression, how to implement it in Python, and learn about Hyperparameter tuning of Linear regression? Well, here we go! A linear regression algorithm in machine learning is a simple regression algorithm that deals with continuous output values. It is a method for predicting a goal value utilizing … Read more
Do you want to know how the random state in sklearn module works and how it affects the formation of clusters? Well, here we go! As we know, machine learning is all about data manipulation. Mostly, we divide the data into testing and training parts in order to evaluate the performance of the model. To … Read more
Sklearn KNN algorithm is a supervised and lazy learning algorithm mainly used to handle classification problems. It is easy to implement and understand but has the major drawback of becoming significantly slow as the size of that data in use grows. It can be used for binary and multi-class classification. Sklearn KNN algorithm is known … Read more
Stock price prediction using machine learning is a difficult task, as the future course of a stock price is often influenced by several factors that are difficult to predict. In recent years, machine learning has become a popular tool for stock price prediction. Machine learning is a form of artificial intelligence that allows computers to … Read more
If you want to have a clear and in-depth understanding of hyperparameter tuning of Catboost in Machine Learning using various methods, well here we go. We will use the custom tuning method and GridSearchCV method to find the optimum values for the parameters of the Catboost algorithm. Catboost is the most recent boosting algorithm that … Read more
Investors purchase and sell company shares on the stock market. Companies provide shares and other securities for trading on a series of exchanges. Additionally, it incorporates over-the-counter (OTC) markets where investors conduct direct securities transactions with one another (rather than through an exchange). So, It is always important to know how to analyze the stock … Read more
Sklearn one hot encoder or one hot encoding is a process of converting categorical values in the dataset to numeric values so that the Machine learning model can understand and interpret the dataset. This step is part of data preprocessing. In this article, we will learn how we can use Sklearn one hot encoder to … Read more
A Pickle is a module in Python that is mostly used to save machine learning and neural network models in the form of binary files. This binary file is known as a pickle. The pickle files have many advantages over a raw model. Once the model is saved as a pickle file, we can easily … Read more
Principal component analysis in Python (PCA) is one of the best and simplest techniques for dimensionality reduction. Dimensionality reduction is simply the transfer of data from high dimensions to low dimensions by retaining all the important attributes and features. The PCA algorithms transform the highly correlated attributes into simple linear uncorrelated ones. In this article, … Read more
Sklearn standardscaler converts the numeric data to a standard scale which is then easy for the machine learning model to analyze. It has been observed that machine learning models perform better when the data is scaled in some specific range, especially the algorithms that are highly dependent on the weight of the input values like … Read more