Deep Learning MasterClass – (Free Course)

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What you’ll learn

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

This course includes:

  • 4.5 hours on-demand video
  • 43 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of completion

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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There are different types of deep learning models, such as feedforward neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and many more. Each type of model is suited for a different type of problem, and the choice of model will depend on the specific task and the type of data that is available.

IN THIS COURSE YOU WILL LEARN :

  • 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…

How to Get this course FREE?

Note: The udemy Courses Will be free for a Maximum of 1000 Learners can use the promo code AND Get this course 100% Free. After that, you will get this course at a discounted price. (Still, It’s a good deal for you to get this course at a discounted price).

External links may contain affiliate links, meaning we get a commission if you decide to make a purchase. Read our disclosure.

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