最新消息:请大家多多支持

Apache Spark Deep Learning Advanced Recipes

教程/Tutorials dsgsd 176浏览 0评论



MP4 | Video: AVC 1920×1080 | Audio: AAC 48KHz 2ch | Duration: 1 hour 35 minutes | English | 624 MB

Video Description
In this video course, you’ll work through specific recipes to generate outcomes for deep learning algorithms—without getting bogged down in theory. From using LSTMs in generative networks to creating a movie recommendation engine, this course tackles both common and not so common problems so you can perform deep learning in a distributed environment.
In addition, you’ll get access to deep learning code within Spark that you can reuse to answer similar problems or tweak to answer slightly different problems. You’ll learn how to predict real estate value using XGBoost. You’ll also explore how to create a movie recommendation engine using popular libraries such as TensorFlow and Keras. By the end of the course, you’ll have the expertise to train and deploy efficient deep learning models on Apache Spark.

Style and Approach
This course includes practical, easy-to-understand solutions on how you can implement the popular deep learning libraries such as TensorFlow and Keras to train your deep learning models on Apache Spark.

Table of Contents
USING LSTMS IN GENERATIVE NETWORKS
REAL ESTATE VALUE PREDICTION USING XGBOOST
FACE RECOGNITION USING DEEP CONVOLUTIONAL NETWORKS
CREATING AND VISUALIZING WORD VECTORS USING WORD2VEC
CREATING A MOVIE RECOMMENDATION ENGINE WITH KERAS

Apache Spark Deep Learning Advanced Recipes

Password/解压密码-0daydown

Download rapidgator
https://rg.to/file/7b65b3c9da1cc48c209e5f658e1d12a4/pasdlar-9fe8-xqzt.part1.rar.html
https://rg.to/file/bf48c58913359577402ee7f322a35d19/pasdlar-9fe8-xqzt.part2.rar.html

Download nitroflare
http://nitroflare.com/view/CED645E1754BC99/pasdlar-9fe8-xqzt.part1.rar
http://nitroflare.com/view/6C5FB6E6FC55F4F/pasdlar-9fe8-xqzt.part2.rar

Download 百度云

你是VIP 1个月(1 month)赞助会员,

资源下载此资源仅限VIP下载,请先

转载请注明:0daytown » Apache Spark Deep Learning Advanced Recipes

您必须 登录 才能发表评论!