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Machine Learning Mastery With Python

Machine Learning Mastery With Python
Author: Jason Brownlee
Publisher: Machine Learning Mastery
Total Pages: 177
Release: 2016-04-08
Genre: Computers
ISBN:

Download Machine Learning Mastery With Python Book in PDF, ePub and Kindle

The Python ecosystem with scikit-learn and pandas is required for operational machine learning. Python is the rising platform for professional machine learning because you can use the same code to explore different models in R&D then deploy it directly to production. In this Ebook, learn exactly how to get started and apply machine learning using the Python ecosystem.


Deep Learning With Python

Deep Learning With Python
Author: Jason Brownlee
Publisher: Machine Learning Mastery
Total Pages: 266
Release: 2016-05-13
Genre: Computers
ISBN:

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Deep learning is the most interesting and powerful machine learning technique right now. Top deep learning libraries are available on the Python ecosystem like Theano and TensorFlow. Tap into their power in a few lines of code using Keras, the best-of-breed applied deep learning library. In this Ebook, learn exactly how to get started and apply deep learning to your own machine learning projects.


Imbalanced Classification with Python

Imbalanced Classification with Python
Author: Jason Brownlee
Publisher: Machine Learning Mastery
Total Pages: 463
Release: 2020-01-14
Genre: Computers
ISBN:

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Imbalanced classification are those classification tasks where the distribution of examples across the classes is not equal. Cut through the equations, Greek letters, and confusion, and discover the specialized techniques data preparation techniques, learning algorithms, and performance metrics that you need to know. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover how to confidently develop robust models for your own imbalanced classification projects.


Ensemble Learning Algorithms With Python

Ensemble Learning Algorithms With Python
Author: Jason Brownlee
Publisher: Machine Learning Mastery
Total Pages: 450
Release: 2021-04-26
Genre: Computers
ISBN:

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Predictive performance is the most important concern on many classification and regression problems. Ensemble learning algorithms combine the predictions from multiple models and are designed to perform better than any contributing ensemble member. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover how to confidently and effectively improve predictive modeling performance using ensemble algorithms.


Better Deep Learning

Better Deep Learning
Author: Jason Brownlee
Publisher: Machine Learning Mastery
Total Pages: 575
Release: 2018-12-13
Genre: Computers
ISBN:

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Deep learning neural networks have become easy to define and fit, but are still hard to configure. Discover exactly how to improve the performance of deep learning neural network models on your predictive modeling projects. With clear explanations, standard Python libraries, and step-by-step tutorial lessons, you’ll discover how to better train your models, reduce overfitting, and make more accurate predictions.


Generative Adversarial Networks with Python

Generative Adversarial Networks with Python
Author: Jason Brownlee
Publisher: Machine Learning Mastery
Total Pages: 655
Release: 2019-07-11
Genre: Computers
ISBN:

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Step-by-step tutorials on generative adversarial networks in python for image synthesis and image translation.


Long Short-Term Memory Networks With Python

Long Short-Term Memory Networks With Python
Author: Jason Brownlee
Publisher: Machine Learning Mastery
Total Pages: 245
Release: 2017-07-20
Genre: Computers
ISBN:

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The Long Short-Term Memory network, or LSTM for short, is a type of recurrent neural network that achieves state-of-the-art results on challenging prediction problems. In this laser-focused Ebook, finally cut through the math, research papers and patchwork descriptions about LSTMs. Using clear explanations, standard Python libraries and step-by-step tutorial lessons you will discover what LSTMs are, and how to develop a suite of LSTM models to get the most out of the method on your sequence prediction problems.


Introduction to Time Series Forecasting With Python

Introduction to Time Series Forecasting With Python
Author: Jason Brownlee
Publisher: Machine Learning Mastery
Total Pages: 359
Release: 2017-02-16
Genre: Mathematics
ISBN:

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Time series forecasting is different from other machine learning problems. The key difference is the fixed sequence of observations and the constraints and additional structure this provides. In this Ebook, finally cut through the math and specialized methods for time series forecasting. Using clear explanations, standard Python libraries and step-by-step tutorials you will discover how to load and prepare data, evaluate model skill, and implement forecasting models for time series data.


Data Preparation for Machine Learning

Data Preparation for Machine Learning
Author: Jason Brownlee
Publisher: Machine Learning Mastery
Total Pages: 398
Release: 2020-06-30
Genre: Computers
ISBN:

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Data preparation involves transforming raw data in to a form that can be modeled using machine learning algorithms. Cut through the equations, Greek letters, and confusion, and discover the specialized data preparation techniques that you need to know to get the most out of your data on your next project. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover how to confidently and effectively prepare your data for predictive modeling with machine learning.


Deep Learning for Computer Vision

Deep Learning for Computer Vision
Author: Jason Brownlee
Publisher: Machine Learning Mastery
Total Pages: 564
Release: 2019-04-04
Genre: Computers
ISBN:

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Step-by-step tutorials on deep learning neural networks for computer vision in python with Keras.