Python (Computer program language)
Overview
Works: | 100 works in 90 publications in 90 languages |
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Titles
Python testing cookbook[electronic resource] :over 70 simple but incredibly effective recipes for taking control of automated testing using powerful Python testing tools /
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Foundations of Python network programming[electronic resource] :the comprehensive guide to building network applications with Python /
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Python algorithms[electronic resource] :mastering basic algorithms in the python language /
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Violent python[electronic resource] :a cookbook for hackers, forensic analysts, penetration testers, and security engineers /
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A primer on scientific programming with Python[electronic resource] /
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Beginning Python visualization[electronic resource] :crafting visual transformation scripts /
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Understanding network hacks[electronic resource] :attack and defense with Python /
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Python for signal processing[electronic resource] :featuring IPython notebooks /
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Python forensics[electronic resource] :a workbench for inventing and sharing digital forensic technology /
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An introduction to Python and computer programming[electronic resource] /
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Beginning Python games development[electronic resource] :with Pygame /
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Python data analytics[electronic resource] :data analysis and science using Pandas, matplotlib, and the Python programming language /
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Numerical Python[electronic resource] :a practical techniques approach for industry /
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Numeric computation and statistical data analysis on the Java platform[electronic resource] /
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Python for probability, statistics, and machine learning[electronic resource] /
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Program arcade games[electronic resource] :with Python and Pygame /
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A functional start to computing with Python[electronic resource] /
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Statistics, data mining, and machine learning in astronomy[electronic resource] :a practical Python guide for the analysis of survey data /
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Derivatives analytics with Python[electronic resource] :data analysis, models, simulation, calibration and hedging /
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Machine learning in Python[electronic resource] :essential techniques for predictive analysis /
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Programming for computations - Python[electronic resource] :a gentle introduction to numerical simulations with Python /
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Deep learning step by step with Python :a very gentle introduction to deep neural networks for practical data science /
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Python machine learning :machine learning and deep learning with Python, scikit-learn, and TensorFlow /
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Artificial intelligence with Python :build real-world artificial intelligence applications with Python to intelligently interact with the world around you /
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Python for data analysis :data wrangling with Pandas, NumPy, and IPython /
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OpenCV with Python by example :build real-world computer vision applications and develop cool demos using OpenCV for Python /
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OpenCV computer vision with Python :learn to capture videos, manipulate images, and track objects with Python using the OpenCV Library /
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Learning OpenCV 3 computer vision with Python :unleash the power of computer vision with Python using OpenCV /
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Neuronale Netze selbst programmieren :ein verständlicher Einstieg mit Python /
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Praxiseinstieg Deep Learning :mit Python, Caffe, TensorFlow und Spark eigene Deep-Learning-Anwendungen erstellen /
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Python data science handbook :essential tools for working with data /
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Python recipes handbook[electronic resource] :a problem-solution approach /
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Lean Python[electronic resource] :learn just enough Python to build useful tools /
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Text analytics with Python[electronic resource] :a practical real-world approach to gaining actionable insights from your data /
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Solving PDEs in Python[electronic resource] :the FEniCS tutorial I /
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Comparative approaches to using R and Python for statistical data analysis[electronic resource] /
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Python for tweens and teens :learn computational and algorithmic thinking /
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Hands-on reinforcement learning with Python :master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow /
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Advanced deep learning with Keras :apply deep learning techniques, autoencoders, GANs, variational autoencoders, deep reinforcement learning, policy gradients, and more /
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PyTorch deep learning hands-on :apply modern AI techniques with CNNs, RNNs, GANs, reinforcement learning, and more /
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Deep learning with PyTorch :a practical approach to building neural network models using PyTorch /
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Marketing data science :modeling techniques in predictive analytics with R and Python /
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Hands-on machine learning for algorithmic trading :design and implement investment strategies based on smart algorithms that learn from data using Python /
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3D image reconstruction for CT and PET[electronic resource] :a practical guide with Python /
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A tour of data science[electronic resource] :learn R and Python in parallel /
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Practical numerical and scientific computing with MATLAB and Python[electronic resource] /
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Introduction to modeling and simulation with MATLAB and Python[electronic resource] /
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Computer simulation[electronic resource] :a foundational approach using Python /
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Bite-size Python[electronic resource] :an introduction to Python programming /
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Introduction to deep learning for engineers[electronic resource] :using python and google cloud platform /
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Machine learning in biotechnology and life sciences :build machine learning models using Python and deploy them on the cloud /
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Advanced applications of Python data structures and algorithms[electronic resource] /
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Text analysis with Python[electronic resource] :a research-oriented guide /
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Dynamic system modelling and analysis with MATLAB and Python[electronic resource] :for control engineers /
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Learning genetic algorithms with Python[electronic resource] :empower the performance of machine learning and AI models with the capabilities of a powerful search algorithm /
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Machine learning with Python[electronic resource] :an approach to applied machine learning /
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Python made simple[electronic resource] :learn Python programming in easy steps with examples /
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Python in-depth[electronic resource] :use Python programming features, techniques, and modules to solve everyday problems /
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Hands-on supervised learning with Python[electronic resource] :learn how to solve machine learning problems with supervised learning algorithms using Python /
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Machine learning for beginners[electronic resource] :learn to build machine learning systems using Python /
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Hands-on data analysis and visualization with pandas[electronic resource] :engineer, analyse and visualize data, using powerful Python libraries /
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Machine learning cookbook with Python[electronic resource] :create ML and data analytics projects using some amazing open datasets /
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Practical data science with Jupyter[electronic resource] :explore data cleaning, pre-processing, data wrangling, feature engineering and machine learning using Python and Jupyter /
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Advance core Python programming[electronic resource] :begin your journey to master the world of Python /
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Python data visualization essentials guide[electronic resource] :become a data visualization expert by building strong proficiency in Pandas, Matplotlib, Seaborn, Plotly, Numpy, and Bokeh /
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Applied machine learning solutions with Python[electronic resource] :production-ready ML projects using cutting-edge libraries and powerful statistical techniques /
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An introduction to Python programming[electronic resource] :a practical approach : using Python to solve complex problems with a burst of machine learning /
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A journey to core Python[electronic resource] :experience the applications of tuples, dictionary, lists, operators, loops, indexing, slicing, and matrices /
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Test your skills in Python[electronic resource] :an interactive way to introduce the world of computer programming /
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Programming techniques using Python[electronic resource] :have fun and play with basic and advanced core Python /
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Full stack development with MongoDB[electronic resource] :covers backend, frontend, APIs, and mobile App development using PHP, NodeJS, ExpressJS, Python and react native /
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Enterprise automation with Python[electronic resource] :automate Excel, web, documents, emails, and various workloads with easy-to-code Python scripts /
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Subjects