This documentation is prepared for those who want to learn Python programming for data science. Here, you will find a comprehensive guide covering various topics from fundamental Python skills to data processing, analysis, and visualization. We aim to provide you with practical knowledge through code examples, applications, and explanations. By exploring the project files and trying out the examples, you will gain proficiency in Python for data science.
Welcome to the CRM Analytics! This repository is designed to help you understand and implement analytical techniques in Customer Relationship Management (CRM). We will explore various methods to analyze customer data, extract insights, and improve customer interactions. The code examples and case studies included here will enhance your analytical skills in the CRM domain.
In this repository, we focus on Measurement Problems encountered in various fields. Measurement plays a crucial role in data analysis, and understanding the challenges associated with it is essential for accurate interpretations. Here, you will find discussions on different measurement issues, practical solutions, and their implications. By going through the materials and examples, you will be better equipped to handle measurement problems in your projects.
Welcome to Recommender Systems! This repository is dedicated to understanding and building recommendation algorithms. Recommender systems are vital in suggesting personalized content to users, and here, we explore different approaches to develop effective recommendation engines. Through hands-on examples and implementation, you will learn how to create recommendation systems that cater to user preferences.
Feature Engineering is a critical aspect of data preprocessing and model development. This repository aims to cover various techniques and best practices for Feature Engineering. Understanding how to extract and select meaningful features from raw data can significantly impact the performance of machine learning models. Here, we provide examples and use cases to improve your feature engineering skills.
Welcome to the Machine Learning repository! Here, we dive into the exciting world of machine learning algorithms and techniques. From supervised to unsupervised learning, we explore different ML models and applications. Understanding the theoretical foundations and hands-on implementation will enable you to solve real-world problems using machine learning.
This repository focuses on MS SQL (Microsoft SQL Server), a widely used relational database management system. Here, you will find SQL queries, tutorials, and best practices to work with MS SQL databases. Whether you are a beginner or an experienced SQL user, this repository will offer valuable insights into managing and querying databases using MS SQL.