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Data science is a category that covers a wide range of topics related to the analysis and interpretation of data. This category may include keywords such as data mining, machine learning, artificial intelligence, statistical analysis, data visualization, big data, predictive modeling, and data engineering.
In this category, you can find articles, resources, and insights related to data science, including best practices, tools, and techniques used by data scientists. Whether you are a beginner or an experienced practitioner, this category can help you stay up-to-date with the latest trends and techniques in data science. You can also find tutorials, case studies, and examples of real-world applications of data science in various fields, such as healthcare, finance, marketing, and more.
In this interesting post, we will explore two terms we often hear from data scientists i.e. Extrapolation & Interpolation. When we get access to data points, we try to present all the information that can be useful. Let’s start exploring this bit from the AI universe. Interpolation vs Extrapolation The prefix inter- means between, and … Read more
Python is one of the most popular programming languages in the world of data science. It provides a variety of tools and packages for data cleaning and preparation. In this post, you’ll find crucial and commonly used Python Snippets for Data Cleaning and Preparation in the fields of AI, ML, and data science. Python Snippets … Read more
Missing data is a common issue in datasets, and can affect the accuracy of any analysis. It is important to handle missing data appropriately in order to avoid biased results. One way to handle missing data is through imputation, which involves filling in missing values with estimated values based on the available data. In this … Read more
When it comes to machine learning, understanding the difference between two sets of data is key. This is where KL divergence, or Kullback-Leibler divergence, comes in. KL divergence in machine learning is a powerful concept that can help us compare two probability distributions, and it has many applications, from detecting anomalies in data to improving … Read more
As AI/ML technologies continue to rapidly develop, it is essential that AI/ML product managers are equipped with the right set of skills and expertise to meet customer needs and deliver value. AI/ML product management involves working closely with engineers, designers, and data scientists to develop and bring AI/ML products to market. The Importance of Keeping … Read more