This repository accompanies Machine Learning Applications Using Python by Puneet Mathur (Apress, 2019). Download the files as a zip using the green button, or clone the repository to your machine ...

After working on the model building, the next step in the machine learning life cycle is usually the deployment in the real-world scenario to perform actionable tasks.In most cases, the model is ...

Machine Learning Theory and Applications delves into the realm of machine learning and deep learning, exploring their practical applications by comprehending mathematical concepts and implementing ...

This process is known as model tuning and is an integral part of the machine learning workflow. Also read: Top 7 Trends in Software Product Design for 2022. Python Libraries and Tools. There are ...

Python has a plethora of machine learning libraries, but the top 5 libraries are TensorFlow, Keras, PyTorch, Scikit-learn, and Pandas. These libraries offer a wide range of tools for various ...

Applebaum noted that Python, a general-purpose programming language, is built into Ignition and includes libraries for machine learning applications. She added that new templates are being included in ...

If you’re doing work in statistics, data science, or machine learning, the odds are high you’re using Python. And for good reason, too: The rich ecosystem of libraries and tooling, and the ...

Learn about some of the best Python libraries for programming Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL).

TensorFlow is a Python-friendly open source library for developing machine learning applications and neural networks. Here's what you need to know about TensorFlow. Credit: KTSimage / Getty Images ...

We can use python for developing desktop GUI applications, websites and web applications. The simple rules of python allow you to express concepts without writing additional code. Machine Learning- ...