Deep Learning MasterClass

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What you’ll learn:

• You will learn the complete life cycle of a Data Science Project with Machine Learning and Deep Learning.
• Learn about different Neural Networks like ANN, CNN and RNN.
• Learn about pandas, numpy, matplotlib, sklearn, tensorflow that are some of the most important python libraries used in Data Science, ML and DL.
• You will build practical projects like Gold Price Prediction, Image Class Prediction and Stock Price Prediction using different Neural

Description:

Deep learning is a subfield of machine learning that is focused on building neural networks with many layers, known as deep neural networks. These networks are typically composed of multiple layers of interconnected “neurons” or “units”, which are simple mathematical functions that process information. The layers in a deep neural network are organized in a hierarchical manner, with lower layers processing basic features and higher layers combining these features to represent more abstract concepts.

Deep learning models are trained using large amounts of data and powerful computational resources, such as graphics processing units (GPUs). Training deep learning models can be computationally intensive, but the models can achieve state-of-the-art performance on a wide range of tasks, including image classification, natural language processing, speech recognition, and many others.

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• Complete Life Cycle of Data Science Project.
• Important Data Science Libraries like Pandas, Numpy, Matplotlib, Seaborn, sklearn etc…
• How to choose appropriate Machine Learning or Deep Learning Model for your project
• Machine Learning Fundamentals
• Regression and Classification in Machine Learning
• Artificial Neural Networks (ANN)
• Convolutional Neural Networks (CNN)
• Recurrent Neural Networks (RNN)
• Tensorflow and Keras
• Different projects like Gold Price Prediction, Stock Price Prediction, Image Classification etc…

Who this course is for:

• Anyone who wants to get started with Deep Learning.
• Data Science and ML folks who want to learn about Neural Networks and Deep Learning.

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