Data science is analyzing the raw data collected from different sources and making that data into useful information needed for the organization. It is vital to analyze a large amount of raw data into something meaningful and extract the valuable information necessary for the different purposes of the organization, such as marketing, sales, and decision-making. Join the Data Science Course in Chennai to learn about data science.
Retrogression. Assume you are a deals director trying to read the coming month's deals.
Decision tree. Visit: Data Science Course in Pune
- Regression Analysis: This technique is used to establish the relationship between a dependent variable and one or more independent variables. It is commonly used for predictive modelling and forecasting.
- Classification:This technique is used to categorize data into different classes or groups. It is often used in image and speech recognition and in spam detection.
- Clustering: This technique is used to group data into clusters based on similarities between data points. It is often used in customer segmentation and anomaly detection.
- Association Rules:This technique is used to discover relationships between variables in a large dataset. It is often used in market basket analysis, to identify products that are frequently purchased together.
- Time Series Analysis:This technique is used to analyze and predict trends in time-dependent data. It is often used in finance, economics, and weather forecasting.
- Natural Language Processing:This technique is used to analyze and understand human language. It is often used in sentiment analysis, chatbots, and language translation.
- Deep Learning: This technique is used for complex pattern recognition and prediction, using artificial neural networks. It is often used in image and speech recognition, and in natural language processing.
- Dimensionality Reduction:This technique is used to reduce the number of variables in a dataset while retaining the most important information. It is often used in data visualization and feature selection.