【机器学习】Machine learning – OpenCV based IOT using Raspberry pi

MP4 |视频:h264，1280×720 |音频:AAC，44.1 KHz，2 Ch
语言：英语+中英文字幕（云桥网络 机译） |时长:44节课(4h 3m) |大小解压后:3.39 GB 含课程文件
借助物联网了解监督学习(计算机视觉)。行业需求不断增长的独特课程

你会学到:
使用开放式CV的监督学习
使用树莓皮的物联网
通过与树莓Pi接口配置和获取传感器数据
为IOT应用开发语音控制接口
监督学习如何在IOT应用中使用


要求
基本编程知识，尤其是Python和Linux命令行命令
对电子元件、电路有基本了解
覆盆子Pi 3板，220欧姆电阻器，1个Uf电容器，LDR传感器，发光二极管，一些跳线电缆

描述
你会发现课程在监督机器学习课程-开放简历一般为计算机。但是，你很难找到一门涵盖基于监督机器学习输出的物联网的综合课程。实际上，对于机器学习来说，当它处理模拟数据时，实时没有任何意义。从传感器或应用程序中获取实时数据会带来自身的挑战，这在学习机器学习时通常会被忽略。

这个独特的封面涵盖了监督机器学习和使用树莓pi的物联网。

对这些类型应用程序的需求越来越大，例如:

楼宇自动化-当有人在场时，打开电气设备，如照明和温度控制仪表。

基于员工自动识别的考勤标记。

确定免费停车场。

识别汽车牌照。

预防犯罪-识别有犯罪记录的人。

还有更多。

所有这些都是基于监督学习技术和IOT的结合。

因此，本课程涵盖了从建筑自动化角度与IOT相结合的监督学习。一旦参与者清楚了这个概念，他们就可以为上面列出的其他应用程序或其他机器学习算法开发/扩展它。

此外，语音控制IOT应用程序也在快速增长。本课程还涵盖了与使用树莓pi和其他开源软件和平台(如OPEN CV、谷歌助手、Ada水果输入输出平台、IFTTT)构建基于语音的IOT应用程序相关的主题。

快乐学习！！！

这门课是给谁的
初学者有兴趣了解机器学习，特别是监督机器学习。
有兴趣学习物联网吗
那些想知道监督机器学习如何应用于IOT应用的人
有计算机科学和电子学背景的学生


MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 44 lectures (4h 3m) | Size: 3.1 GB
Learn about Supervised Learning (computer vision) with Internet of things. A unique course with growing industry demand

What you’ll learn:
Supervised learning using OPEN CV
Internet of things using Raspberry Pi
Configuring and acquiring data from sensor(s) by interfacing with Raspberry Pi
Developing voice control interface for IOT application
How Supervised learning can be used in IOT applications

Requirements
Basic Programming knowledge particularly Python & Linux command line commands
Basic understanding of Electronic component , circuits
Raspberry Pi 3 board, 220 ohm resistors, 1 Uf capacitor, LDR sensor, LED, some jumper cables

Description
You will find course in Supervised machine learning course – OPEN CV generally for computer. But, hardly you will find an integrated course which covers Internet of things based on supervised machine learning output. In really, for machine learning in real time has no meaning when it works with simulated data. Getting real time data be in from Sensor or an Application, poses it own challenges and this is generally over looked while learning about machine learning.

This unique covers covers both Supervised machine learning and Internet of things using Raspberry pi.

There is a growing demand for these kind of application, For example:

Building automation – Switch on Electrical device such as lighting and temperature control instrument when human being in present.

Attendance marking based on automatically identification of an employee.

Identify parking free parking lots.

Identify number plate in car.

Prevent Crime – Identify a person with criminal record.

And many more.

All these operate on combination of supervised learning technique coupled with IOT.

Hence this course covers supervised learning coupled with IOT from a building building automation perspective. Once participants are clear about the concept they can then develop /extend it for other applications listed above or on the other machine learning algorithms.

Additionally, voice control IOT application is also growing at a rapid pace. This course also covers topic related to building voice based IOT application using Raspberry pi and other open source software and platforms like OPEN CV, Google assistant, Adafruit IO platform, IFTTT.

Happy learning!!!

Who this course is for
Beginner interested to understand Machine Learning particularly Supervised Machine learning.
Interested to learn Internet of things
Those interested to know as how Supervisory machine learning can be used IOT application
Students with background in Computer Science and Electronics
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