Efficient Learning Machines: Theories, Concepts, and Applications for Engineers and System Designers

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Sign In Register Help Cart. Cart items. Toggle navigation. Search Results Results 1 -5 of 5. Berkeley: Apress. Apress, New and in stock. Ships with Tracking Number! May not contain Access Codes or Supplements. May be ex-library. Buy with confidence, excellent customer service! Efficient Learning Machines Mariette Awad and. Product details Paperback: pages Publisher: Springer Nature; 1st ed. Image-to-Image Translation with Conditional Adversarial Networks - Implementation of image to image pix2pix translation from the paper by isola et al.


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This is aimed at absorbing the much of the ML workflow, unlike other packages like nilearn and pymvpa, which require you to learn their API and code to produce anything useful. Pyevolve - Genetic algorithm framework. SKLL - A wrapper around scikit-learn that makes it simpler to conduct experiments. Advances in Neural Information Processing Systems, TensorFlow - Open source software library for numerical computation using data flow graphs. Timbl is an elaborate k-Nearest Neighbours machine learning toolkit. Annoy - Approximate nearest neighbours implementation.

TPOT - Tool that automatically creates and optimizes machine learning pipelines using genetic programming. Consider it your personal data science assistant, automating a tedious part of machine learning.

Efficient Learning Machines

Orange - Open source data visualization and data analysis for novices and experts. REP - an IPython-based environment for conducting data-driven research in a consistent and reproducible way. REP is not trying to substitute scikit-learn, but extends it and provides better user experience.

Xcessiv - A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling. Aims to showcase the nuts and bolts of ML in an accessible way. Edward - A library for probabilistic modeling, inference, and criticism. Built on top of TensorFlow. CatBoost - General purpose gradient boosting on decision trees library with categorical features support out of the box. Parris - Parris, the automated infrastructure setup tool for machine learning algorithms.

Turi Create - Machine learning from Apple. Turi Create simplifies the development of custom machine learning models. You don't have to be a machine learning expert to add recommendations, object detection, image classification, image similarity or activity classification to your app. Microsoft Recommenders : Examples and best practices for building recommendation systems, provided as Jupyter notebooks. The repo contains some of the latest state of the art algorithms from Microsoft Research as well as from other companies and institutions. StellarGraph : Machine Learning on Graphs, a Python library for machine learning on graph-structured network-structured data.

Neuraxle : A framework providing the right abstractions to ease research, development, and deployment of your ML pipelines. Cornac - A comparative framework for multimodal recommender systems with a focus on models leveraging auxiliary data. NumPy - A fundamental package for scientific computing with Python. Mars - A tensor-based framework for large-scale data computation which often regarded as a parallel and distributed version of NumPy.

NetworkX - A high-productivity software for complex networks. Pandas - A library providing high-performance, easy-to-use data structures and data analysis tools. SymPy - A Python library for symbolic mathematics. PyDexter - Simple plotting for Python. Wrapper for D3xterjs; easily render charts in-browser.

Seaborn - A python visualization library based on matplotlib. Superset - A data exploration platform designed to be visual, intuitive, and interactive.

Bibliographic Information

Dora - Tools for exploratory data analysis in Python. Ruffus - Computation Pipeline library for python. Bowtie - A dashboard library for interactive visualizations using flask socketio and react. It is able to explain any black box classifier, with two or more classes. PyCM - PyCM is a multi-class confusion matrix library written in Python that supports both input data vectors and direct matrix, and a proper tool for post-classification model evaluation that supports most classes and overall statistics parameters Dash - A framework for creating analytical web applications built on top of Plotly.

TensorWatch - Debugging and visualization tool for machine learning and data science. It extensively leverages Jupyter Notebook to show real-time visualizations of data in running processes such as machine learning training. Diffusion Segmentation - A collection of image segmentation algorithms based on diffusion methods.

Scipy Tutorials - SciPy tutorials. This is outdated, check out scipy-lecture-notes.

Efficient Learning Machines | SpringerLink

Crab - A recommendation engine library for Python. Sentence Similarity between two JP Sentences. Sentiment Analysis of Japanese Text. Python Programming for the Humanities - Course for Python programming for the Humanities, assuming no prior knowledge. GreatCircle - Library for calculating great circle distance. Optunity examples - Examples demonstrating how to use Optunity in synergy with machine learning libraries.

Dive into Machine Learning with Python Jupyter notebook and scikit-learn - "I learned Python by hacking first, and getting serious later. I wanted to do this with Machine Learning. If this is your style, join me in getting a bit ahead of yourself. It features interactive, node-by-node debugging and visualization for TensorFlow. Introduction to machine learning with scikit-learn - IPython notebooks from Data School's video tutorials on scikit-learn.

Neuron - Neuron is simple class for time series predictions.


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Cats - Code for Kaggle Dogs vs. Cats competition. Kaggle Gender - A Kaggle competition: discriminate gender based on handwriting.

Table of contents

Kaggle Merck - Merck challenge at Kaggle. Kaggle Stackoverflow - Predicting closed questions on Stack Overflow. Its primary purpose is to act as a testbed for research in artificial intelligence, especially deep reinforcement learning.

yoku-nemureru.com/wp-content/application-spy/1210-cellphone-locate-tool.php Gym - OpenAI Gym is a toolkit for developing and comparing reinforcement learning algorithms. AI - Serpent. AI is a game agent framework that allows you to turn any video game you own into a sandbox to develop AI and machine learning experiments. For both researchers and hobbyists.

Lecture 11.1 — Machine Learning System Design - Prioritizing What To Work On — [ Andrew Ng]

It is primarily intended for research in machine visual learning, and deep reinforcement learning, in particular. Twitter-text-rb - A library that does auto linking and extraction of usernames, lists and hashtags in tweets. SciRuby Glean - A data management tool for humans. Get list of pretty much anything stop words, countries, non words in txt, json or hash. Available under the MIT license.

R General-Purpose Machine Learning ahaz - ahaz: Regularization for semiparametric additive hazards regression. Boruta - Boruta: A wrapper algorithm for all-relevant feature selection. C50 - C C5. L0Learn - L0Learn: Fast algorithms for best subset selection. Machine Learning For Hackers maptree - maptree: Mapping, pruning, and graphing tree models. NN and SVM in classification and regression. SuperLearner - Multi-algorithm ensemble learning packages. Optunity is written in Python but interfaces seamlessly to R.

However, some measure of interactivity can be achieved with htmlwidgets bringing javascript libraries to R. These include, plotly , dygraphs , highcharter , and several others. SAS General-Purpose Machine Learning Visual Data Mining and Machine Learning - Interactive, automated, and programmatic modeling with the latest machine learning algorithms in and end-to-end analytics environment, from data prep to deployment.

Free trial available. Enterprise Miner - Data mining and machine learning that creates deployable models using a GUI or code. Factory Miner - Automatically creates deployable machine learning models across numerous market or customer segments using a GUI. Breeze - Breeze is a numerical processing library for Scala.

Chalk - Chalk is a natural language processing library.

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