Automation is a key component of enterprises' push to transform their operations, and a driver of that automation is data science. However, there are many misconceptions that still arise when it comes todata science, AI and machine learning, specifically when it comes to data projects. To help...
Fraud detectionis one of the most important Data Science projects and also one of the most challenging for final-year students. With many forms of online and digital transactions being used widely, the chances of them being fraudulent are increasingly high. Since any form of digital transaction g...
Jules J.Berman, inPrinciples and Practice of Big Data (Second Edition), 2018 Abstract ManyBig Dataprojects have ended in disaster: either the resource failed to materialize, or the resource failed to meet its intended goals, or the data in the resource failed to yield solutions, or the solut...
Data Science in Practicedoi:10.1093/jrsssa/qnae081Hossain Md MoyazzemJournal of the Royal Statistical Society Series A: Statistics in Society
Learning a little each day adds up. Research shows that students who make learning a habit are more likely to reach their goals. Challenges are ideal for building new habits. Why Challenges Practice ML Put your data science knowledge into practice and work on exciting machine learning problems ...
Principles and Practice of Big Data: Preparing, Sharing, and Analyzing Complex Information, Second Edition updates and expands on the first edition, bringing a set of techniques and algorithms that are tailored to Big Data projects. The book stresses the point that most data analyses conducted on...
Public Datasets: Kaggle provides access to a large number of public datasets, which can be used for practice, research, or competition submissions. Notebooks: Kaggle provides a cloud-based Jupyter notebook environment for data science and machine learning, which allows users to easily write, run,...
Awesome Data Science with Python A curated list of awesome resources for practicing data science using Python, including not only libraries, but also links to tutorials, code snippets, blog posts and talks. Core pandas - Data structures built on top of numpy. scikit-learn - Core ML library, ...
I am a freelance data analyst, collaborating with companies and organisations worldwide in data science projects. I am also a data science instructor with 2+ experience. I regularly write data-science-related articles in English and Spanish, some of which have been published on established website...
Practice every day and gain a definitive edge: In this data science for Beginners tutorial, you learned about data science, but that would not be enough. If you want to build your skills and hone them to perfection, then you need to practice every day. To be a data scientist, you need...