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Master the top 7 statistical techniques for better data analysis

Data Science Dojo

Get ahead in data analysis with our summary of the top 7 must-know statistical techniques. Master these tools for better insights and results. While the field of statistical inference is fascinating, many people have a tough time grasping its subtleties.

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Top 10 Python packages you need to master to maximize your coding productivity

Data Science Dojo

One of the main reasons for its popularity is the vast array of libraries and packages available for data manipulation, analysis, and visualization. It supports large, multi-dimensional arrays and matrices of numerical data, as well as a large library of mathematical functions to operate on these arrays.

Python 329
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Top 10 Python packages you need to master to maximize your coding productivity

Data Science Dojo

One of the main reasons for its popularity is the vast array of libraries and packages available for data manipulation, analysis, and visualization. It supports large, multi-dimensional arrays and matrices of numerical data, as well as a large library of mathematical functions to operate on these arrays.

Python 195
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Five machine learning types to know

IBM Journey to AI blog

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. What is machine learning?

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From prediction to prevention: Machines’ struggle to save our hearts

Dataconomy

Apart from many areas in our lives, hybrid machine learning techniques can help us with effective heart disease prediction. So how can the technology of our time, machine learning, be used to improve the quality and length of human life? According to the World Health Organization , heart disease takes an estimated 17.9

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Anomaly detection in machine learning: Finding outliers for optimization of business functions

IBM Journey to AI blog

Anomalies are not inherently bad, but being aware of them, and having data to put them in context, is integral to understanding and protecting your business. The challenge for IT departments working in data science is making sense of expanding and ever-changing data points.

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Data science vs. machine learning: What’s the difference?

IBM Journey to AI blog

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? What is machine learning?