Build Multilayer Perceptron Models with Keras
3,715명이 이미 등록했습니다.
3,715명이 이미 등록했습니다.
In this 45-minute long project-based course, you will build and train a multilayer perceptronl (MLP) model using Keras, with Tensorflow as its backend. We will be working with the Reuters dataset, a set of short newswires and their topics, published by Reuters in 1986. It's a very simple, widely used toy dataset for text classification. There are 46 different topics, some of which are more represented than others. But each topic has at least 10 examples in the training set. So in this project, you will build a MLP feed-forward neural network to classify Reuters newswires into 46 different mutually-exclusive topics. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and Keras pre-installed. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
작업 영역이 있는 분할 화면으로 재생되는 동영상에서 강사는 다음을 단계별로 안내합니다.
작업 영역은 브라우저에 바로 로드되는 클라우드 데스크톱으로, 다운로드할 필요가 없습니다.
분할 화면 동영상에서 강사가 프로젝트를 단계별로 안내해 줍니다.
VD 제공2020년 5월 14일
Nice project, could be a bit better with more written instructions. But still, learnt a lot!
BB 제공2020년 7월 16일
Professor taught course quite well and work load was bearable. Though it was soooooo easy course I would suggest Professor to increase the difficulty level by adding another week.
CM 제공2021년 10월 3일
This course is like learning to cook with microwave. Sufficiently easy for a great start. Can be followed up with course recommendations on data preprocessing, model tuning and evaluation, etc.
AM 제공2020년 5월 19일
Nice project for practice. For those who are beginner it is very good for them to do practice.