Packt – scikit-learn Recipes-ZH

Packt – scikit-learn Recipes-ZH
English | Size: 494.21 MB
Category: Tutorial

Python is quickly becoming the go-to language for analysts and data scientists due to its simplicity and flexibility, and within the Python data space, scikit-learn is the unequivocal choice for machine learning. This book includes walk throughs and solutions to the common as well as the not-so-common problems in machine learning, and how scikit-learn can be leveraged to perform various machine learning tasks effectively.
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Pluralsight – Building Neural Networks with scikit-learn

Pluralsight – Building Neural Networks with scikit-learn-XQZT
English | Size: 296.29 MB
Category: Tutorial


This course covers all the important aspects of support currently available in scikit-learn for the construction and training of neural networks, including the perceptron, MLPClassifier, and MLPRegressor, as well as Restricted Boltzmann Machines. [Read more…]

Pluralsight – Preparing Data for Modeling with scikit-learn

Pluralsight – Preparing Data for Modeling with scikit-learn-XQZT
English | Size: 535.24 MB
Category: Tutorial


This course covers important steps in the pre-processing of data, including standardization, normalization, novelty and outlier detection, pre-processing image and text data, as well as explicit kernel approximations such as the RBF and Nystroem methods. [Read more…]

Pluralsight – Employing Ensemble Methods with scikit-learn

Pluralsight – Employing Ensemble Methods with scikit-learn-XQZT
English | Size: 252.01 MB
Category: Tutorial


This course covers the theoretical and practical aspects of building ensemble learning solutions in scikit-learn; from random forests built using bagging and pasting to adaptive and gradient boosting and model stacking and hyperparameter tuning.
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PluralSight – Building Classification Models with scikit-learn

PluralSight – Building Classification Models with scikit-learn-ViGOROUS
English | Size: 303.18 MB
Category: Tutorial


Perhaps the most ground-breaking advances in machine learning have come from applying machine learning to classification problems. In this course, Building Classification Models with scikit-learn you will gain the ability to enumerate the different types of classification algorithms and correctly implement them in scikit-learn. First, you will learn what classification seeks to achieve, and how to evaluate classifiers using accuracy, precision, recall, and ROC curves. Next, you will discover how to implement various classification techniques such as logistic regression, and Naive Bayes classification. You will then understand other more advanced forms of classification, including those using Support Vector Machines, Decision Trees and Stochastic Gradient Descent. Finally, you will round out the course by understanding the hyperparameters that these various classification models possess, and how these can be optimized. When you’re finished with this course, you will have the skills and knowledge to select the correct classification algorithm based on the problem you are trying to solve, and also implement it correctly using scikit-learn. [Read more…]

Packtpub – Hands-on NLP with NLTK and Scikit-learn

Packtpub – Hands-on NLP with NLTK and Scikit-learn
English | Size: 716.44 MB
Category: Programming | E-learning | others

There is an overflow of text data online nowadays. As a Python developer, you need to create a new solution using Natural Language Processing for your next project. Your colleagues depend on you to monetize gigabytes of unstructured text data. What do you do?
Hands-on NLP with NLTK and scikit-learn is the answer. This course puts you right on the spot, starting off with building a spam classifier in our first video. At the end of the course, you are going to walk away with three NLP applications: a spam filter, a topic classifier, and a sentiment analyzer. There is no need for fancy mathematical theory, just plain English explanations of core NLP concepts and how to apply those using Python libraries.Taking this course will help you to precisely create new applications with Python and NLP. You will be able to build actual solutions backed by machine learning and NLP processing models with ease. [Read more…]

Packt – Hands-on Scikit-learn for Machine Learning [Video]

Packt – Hands-on Scikit-learn for Machine Learning [Video]
English | Size: 1.59 GB
Category: CBTs

Scikit-learn is arguably the most popular Python library for Machine Learning today. Thousands of Data Scientists and Machine Learning practitioners use it for day to day tasks throughout a Machine Learning project’s life cycle. Due to its popularity and coverage of a wide variety of ML models and built-in utilities, jobs for Scikit-learn are in high demand, both in industry and academia.
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Packt Publiching – Advanced Predictive Techniques with Scikit-Learn and TensorFlow

Packt Publiching – Advanced Predictive Techniques with Scikit-Learn and TensorFlow
English | Size: 910.35 MB
Category: Tutorial

This course presents some of the most advanced Predictive Analytics tools, models, and techniques currently having a big impact on every industry. The main goal is to show the viewer how to improve the performance of predictive models-firstly, by showing how to build more complex models and secondly, by showing how to use related techniques that dramatically improve the quality of predictive models.
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