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A collection of data analysis and visualization projects designed to uncover insights from diverse datasets. These projects include analyses on COVID-19 trends, stock trading patterns, housing market prices, IoT data, and more, showcasing the power of data-driven storytelling.
Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Here are 26,364 public repositories matching this topic...
Discover a portfolio of comprehensive data analytics projects featuring SQL, Python, and Power BI. Uncover critical insights and data-driven solutions to real-world challenges through advanced data extraction, in-depth analysis, and dynamic visualization. Perfect for both novices and seasoned professionals aiming to elevate their data analytics.
The above course provides newbies with an overview of data analytics and the key steps in the process. In this course, you will learn how to differentiate between different data roles such as Data Engineer, Data Analyst, Data Scientist, Business Analyst, and Business Intelligence Analyst. You will get an insight and be able to describe the ...
30 Μαΐ 2023 · Exploratory Data Analysis (EDA) is the single most important task to conduct at the beginning of every data science project. In essence, it involves thoroughly examining and characterizing your data in order to find its underlying characteristics, possible anomalies, and hidden patterns and relationships.
6 Ιαν 2022 · TensorFlow is an open-source framework for Machine learning and Artificial Intelligence developed by Google Brain Team. The GitHub repository contains various resources to learn and enhance the TensorFlow and Machine Learn skills. You can learn more about TensorFlow through TensorFlow tutorials.
12 Σεπ 2024 · Data analysis is a comprehensive method of inspecting, cleansing, transforming, and modeling data to discover useful information, draw conclusions, and support decision-making. It is a multifaceted process involving various techniques and methodologies to interpret data from various sources in different formats, both structured and unstructured.
