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Mastering TensorFlow 1.x: Advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras
Mastering TensorFlow 1.x: Advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras

Build, scale, and deploy deep neural network models using the star libraries in Python

Key Features

  • Delve into advanced machine learning and deep learning use cases using Tensorflow and Keras
  • Build, deploy, and scale end-to-end deep neural network models in a production...
Java Deep Learning Projects: Implement 10 real-world deep learning applications using Deeplearning4j and open source APIs
Java Deep Learning Projects: Implement 10 real-world deep learning applications using Deeplearning4j and open source APIs

Build and deploy powerful neural network models using the latest Java deep learning libraries

Key Features

  • Understand DL with Java by implementing real-world projects
  • Master implementations of various ANN models and build your own DL systems
  • Develop...
Go Standard Library Cookbook: Over 120 specific ways to make full use of the standard library components in Golang
Go Standard Library Cookbook: Over 120 specific ways to make full use of the standard library components in Golang

Implement solutions by leveraging the power of the GO standard library and reducing dependency on external crates

Key Features

  • Develop high quality, fast and portable applications by leveraging the power of Go Standard Library.
  • Practical recipes that will help you work...
Scala Machine Learning Projects: Build real-world machine learning and deep learning projects with Scala
Scala Machine Learning Projects: Build real-world machine learning and deep learning projects with Scala

Powerful smart applications using deep learning algorithms to dominate numerical computing, deep learning, and functional programming.

Key Features

  • Explore machine learning techniques with prominent open source Scala libraries such as Spark ML, H2O, MXNet, Zeppelin, and DeepLearning4j
  • ...
Numerical Computing with Python: Harness the power of Python to analyze and find hidden patterns in the data
Numerical Computing with Python: Harness the power of Python to analyze and find hidden patterns in the data

Understand, explore, and effectively present data using the powerful data visualization techniques of Python

Key Features

  • Use the power of Pandas and Matplotlib to easily solve data mining issues
  • Understand the basics of statistics to build powerful predictive data...
Monetizing Machine Learning: Quickly Turn Python ML Ideas into Web Applications on the Serverless Cloud
Monetizing Machine Learning: Quickly Turn Python ML Ideas into Web Applications on the Serverless Cloud

Take your Python machine learning ideas and create serverless web applications accessible by anyone with an Internet connection. Some of the most popular serverless cloud providers are covered in this book?Amazon, Microsoft, Google, and PythonAnywhere.

You will work through a series of common Python data science problems...

Jupyter Cookbook: Over 75 recipes to perform interactive computing across Python, R, Scala, Spark, JavaScript, and more
Jupyter Cookbook: Over 75 recipes to perform interactive computing across Python, R, Scala, Spark, JavaScript, and more

Leverage the power of the popular Jupyter notebooks to simplify your data science tasks without any hassle

Key Features

  • Create and share interactive documents with live code, text and visualizations
  • Integrate popular programming languages such as Python, R, Julia, Scala...
Mastering Numerical Computing with NumPy: Master scientific computing and perform complex operations with ease
Mastering Numerical Computing with NumPy: Master scientific computing and perform complex operations with ease

Enhance the power of NumPy and start boosting your scientific computing capabilities

Key Features

  • Grasp all aspects of numerical computing and understand NumPy
  • Explore examples to learn exploratory data analysis (EDA), regression, and clustering
  • Access...
Partial Differential Equations and the Finite Element Method
Partial Differential Equations and the Finite Element Method
A systematic introduction to partial differential equations and modern finite element methods for their efficient numerical solution

Partial Differential Equations and the Finite Element Method provides a much-needed, clear, and systematic introduction to modern theory of partial differential equations (PDEs) and...

Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib
Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib

Leverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy, SciPy, FiPy, matplotlib and more. This fully revised edition, updated with the latest details of each package and changes to Jupyter projects, demonstrates how to numerically compute...

High-performance and Hardware-aware Computing
High-performance and Hardware-aware Computing

High-performance system architectures are increasingly exploiting heterogeneity: multi- and manycore-based systems are complemented by coprocessors, accelerators, and reconfigurable units providing huge computational power. However, applications of scientific interest (e.g. in high-performance computing and numerical simulation) are not yet...

Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning
Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning

This practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you’re comfortable with Python and its libraries, including pandas and scikit-learn, you’ll be able to address specific problems such as loading data, handling text or...

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