Deploying Machine Learning Models as Microservices Using Docker

Deploying Machine Learning Models as Microservices Using Docker
Deploying Machine Learning Models as Microservices Using Docker
MP4 | Video: AVC 1920x1080 | Audio: AAC 48KHz 2ch | Duration: 24M | 825 MB
Genre: eLearning | Language: English

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Author: supnatural | Comment: ( 0 )

An Introduction to Machine Learning Models in Production

An Introduction to Machine Learning Models in Production
An Introduction to Machine Learning Models in Production
MP4 | Video: AVC 1920x1080 | Audio: AAC 48KHz 2ch | Duration: 39M | 1.38 GB
Genre: eLearning | Language: English

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Author: supnatural | Comment: ( 0 )

Training and Exporting Machine Learning Models in Spark

Training and Exporting Machine Learning Models in Spark
Training and Exporting Machine Learning Models in Spark
MP4 | Video: AVC 1920x1080 | Audio: AAC 48KHz 2ch | Duration: 34M | 1.22 GB
Genre: eLearning | Language: English

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Author: supnatural | Comment: ( 0 )

Monitoring and Improving the Performance of Machine Learning Models

Monitoring and Improving the Performance of Machine Learning Models
Monitoring and Improving the Performance of Machine Learning Models
MP4 | Video: AVC 1920x1080 | Audio: AAC 48KHz 2ch | Duration: 35M | 863 MB
Genre: eLearning | Language: English

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Author: supnatural | Comment: ( 0 )

Live Lessons - Deep Learning for Natural Language Processing Applications of Deep Neural Networks to Machine Learning Tasks

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Live Lessons - Deep Learning for Natural Language Processing Applications of Deep Neural Networks to Machine Learning Tasks
English | Size: 8.59 GB
Category: CBTs

An intuitive introduction to processing natural language data with Deep Learning models Deep Learning for Natural Language Processing LiveLessons is an introduction to processing natural language with Deep Learning. These lessons bring intuitive explanations of essential theory to life with interactive, hands-on Jupyter notebook demos. Examples feature Python and Keras, the high-level API for TensorFlow, the most popular Deep Learning library. In the early lessons, specifics of working with natural language data are covered, including how to convert natural language into numerical representations that can be readily processed by machine learning approaches. In the later lessons, state-of-the art Deep Learning architectures are leveraged to make predictions with natural language data.
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Author: minhchick | Comment: ( 0 )

Machine Learning Challenges


Machine Learning Challenges

Joaquin Quinonero-Candela, Ido Dagan, Bernardo Magnini, "Machine Learning Challenges"
English | 2006 | ISBN: 3540334270 | PDF | pages: 473 | 5.3 mb

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Author: New.Life | Comment: ( 0 )

Extending Machine Learning Algorithms

Extending Machine Learning Algorithms
Extending Machine Learning Algorithms
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 3 Hours | 398 MB
Genre: eLearning | Language: English

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Getting Started with MATLAB Machine Learning

Getting Started with MATLAB Machine Learning
Getting Started with MATLAB Machine Learning
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 1 Hour 48M | 2.03 GB
Genre: eLearning | Language: English

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Packt Publishing - Fundamentals of Statistical Modeling and Machine Learning Techniques

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Packt Publishing - Fundamentals of Statistical Modeling and Machine Learning Techniques
English | Size: 386.61 MB
Category: Tutorial

Complex statistics in Machine Learning worry a lot of developers. Knowing statistics helps you build strong Machine Learning models that are optimized for a given problem statement. This video will teach you all it takes to perform complex statistical computations required for Machine Learning. Understand the real-world examples that discuss the statistical side of Machine Learning and familiarize yourself with it. We will discuss the application of frequently used algorithms on various domain problems, using both Python and R programming. We will use libraries such as scikit-learn, NumPy, random Forest and so on. By the end of the course, you will have mastered the required statistics for Machine Learning and will be able to apply your new skills to any sort of industry problem.
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Packt Publishing - Applied Machine Learning and Deep Learning with R

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Packt Publishing - Applied Machine Learning and Deep Learning with R
English | Size: 575.56 MB
Category: CBTs

A step-by-step real world guide on machine learning and deep learning that takes you through the core aspects for building powerful data science applications with the help of the R programming language

In this course, we will examine in detail the R software, which is the most popular statistical programming language of recent years.

You will start with exploring different learning methods, clustering, classification, model evaluation methods and performance metrics. From there, you will dive into the general structure of the clustering algorithms and develop applications in the R environment by using clustering and classification algorithms for real-life problems Next, you will learn to use general definitions about artificial neural networks, and the concept of deep learning will be introduced. The elements of deep learning neural networks, types of deep learning networks, frameworks used for deep learning applications will be addressed and applications will be done with R TensorFlow package. Finally, you will dive into developing machine learning applications with SparkR, and learn to make distributed jobs on SparkR.
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Author: minhchick | Comment: ( 0 )