TensorFlow is popular a library for implementing a range of deep learning solutions but is especially useful for solutions that deal with images. This course will teach you the basics of how to use TensorFlow to implement the most typical scenarios.

In this course, you will learn how you can develop your machine learning workflow using RapidMiner Studio, a data science platform for data preparation, machine learning, and predictive model deployment.

In this course, you will learn how you can develop your machine learning workflow using Weka, an open-source machine learning software for data preparation, machine learning, and predictive model deployment.

TensorFlow is a widely-used data science and machine learning software library. This course will teach you the basics of implementing predictive analytics using TensorFlow, including supervised learning, recommendation, and reinforcement systems.

Learn about fundamental deep learning architectures such as CNNs, RNNs, LSTMs, and GRUs for modeling image and sequential data.

Level up your machine learning skills with tuning methods, advanced models, and dimensionality reduction.

Learn about what transformers are (the T of GPT) and how to work with them using Hugging Face libraries

Learn the foundations of cloud computing across platforms like AWS, Cloud, Azure, and GCP.

Build basic deep learning models in TensorFlow.

Learn about the Hugging Face AI and machine learning platform, and how their tools can streamline ML and AI development.

Improve machine learning models with hyperparameter tuning.

Build the basic language models in Python.