Deep Learning with TensorFlow: Deep Neural Nets in Python

Deep Learning with TensorFlow: Deep Neural Nets in Python

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Deep Learning with TensorFlow: Deep Neural Nets in Python

Deep Learning with TensorFlow: Deep Neural Nets in Python, Leverage Deep Learning and TensorFlow in Python to improve your business! Build deep learning algorithms from scratch

Created by 365 Careers, 365 Careers Team

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What you'll learn
  • Acquire the most important skill data scientists need in their job – Machine and Deep Learning
  • Experience first-hand the unmatched satisfaction of taking big amounts of data and finding complex relationships
  • Create Deep Learning algorithms in Python, using NumPy and TensorFlow
  • Develop a business intuition while coding and solving tasks with big data
  • Get a complete overview of TensorFlow – Google’s cutting-edge deep learning framework
  • Apply Deep Learning to a real-life case with real people, real data, and real insights, helping a business optimize its marketing efforts
  • Acquire the skills companies look for when hiring data scientists
  • Start from the very basics – data, model, objective function, and optimization algorithm
  • Obtain a deep understanding of the deep learning process
  • Learn the mathematics behind a deep learning algorithm, through our course notes
  • Begin with NumPy and transfer to TensorFlow, to see the ML process from different angles
  • Build deep learning algorithms from scratch
  • Unfold the power of deep neural networks
  • Understand backpropagation
  • Gradually study more complex topics such as: underfitting and overfitting, training, validation, n-fold cross validation, testing, early stopping, initialization
  • Learn about optimization techniques like the stochastic gradient descent, batching, momentum, and learning rate schedules
  • Apply each and every topic you learn
  • Implement deep learning functions in Python
  • Speed up algorithms
  • Carry out preprocessing - standardization, normalization, and one-hot encoding
  • Assess the accuracy of deep learning algorithms
  • Fiddle with hyperparameters for better performance

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