A Machine Learning library, also known as a Machine Learning framework, is a collection of procedures and functions developed in a certain programming language.
Keras is an open-source library that works well on both CPU and GPU. It is employed in deep learning, specifically neural networks.
TensorFlow, PyTorch, and scikit-learn are arguably the most popular ML frameworks.
To understand how to do various actions, training datasets must be given into the machine learning algorithm first, followed by validation datasets (or testing datasets) to check that the model is correctly understanding this data.
State the issue as soon as possible.
Put in place data collection mechanisms.
Examine the accuracy of your data.
Format data to ensure consistency.
Trim the data.
Finish data cleansing.
Make new features from current ones.
where is the finaldata.csv
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