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Unlocking data science 101: The essential elements of statistics, Python, models, and more

Data Science Dojo

Machine learning is a field of computer science that uses statistical techniques to build models from data. Some of the most popular Python libraries for data science include: NumPy is a library for numerical computation. SciPy is a library for scientific computing. Pandas is a library for data analysis.

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Five machine learning types to know

IBM Journey to AI blog

Each type and sub-type of ML algorithm has unique benefits and capabilities that teams can leverage for different tasks. What is machine learning? ML is a computer science, data science and artificial intelligence (AI) subset that enables systems to learn and improve from data without additional programming interventions.

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AI Drug Discovery: How It’s Changing the Game

Becoming Human

AI began back in the 1950s as a simple series of “if, then rules” and made its way into healthcare two decades later after more complex algorithms were developed. Machine Learning Machine learning (ML) focuses on training computer algorithms to learn from data and improve their performance, without being explicitly programmed.

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Your Ultimate Guide to Coursera Machine Learning Top Courses

How to Learn Machine Learning

Covering a comprehensive range of topics, the course provides a deep dive into the fundamental principles and practical applications of machine learning algorithms. This professional certificate provides a holistic approach to machine learning, combining theoretical knowledge with practical skills.

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Creating an artificial intelligence 101

Dataconomy

Algorithms:  AI algorithms are used to process the data and extract insights from it. There are several types of AI algorithms, including supervised learning, unsupervised learning, and reinforcement learning. Develop AI models using machine learning or deep learning algorithms.

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

IBM Journey to AI blog

Just as humans can learn through experience rather than merely following instructions, machines can learn by applying tools to data analysis. Machine learning works on a known problem with tools and techniques, creating algorithms that let a machine learn from data through experience and with minimal human intervention.

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Classification vs. Clustering

Pickl AI

Machine Learning is a subset of Artificial Intelligence and Computer Science that makes use of data and algorithms to imitate human learning and improving accuracy. Being an important component of Data Science, the use of statistical methods are crucial in training algorithms in order to make classification.