Udemy - Machine learning - OpenCV based IOT using Raspberry pi

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[ CourseWikia.com ] Udemy - Machine learning - OpenCV based IOT using Raspberry pi
  • Get Bonus Downloads Here.url (0.2 KB)
  • ~Get Your Files Here ! 1. Prerequisite and Course coverage
    • 1. Prerequisite.mp4 (19.2 MB)
    • 1. Prerequisite.srt (0.9 KB)
    • 2. Course coverage.mp4 (58.2 MB)
    • 2. Course coverage.srt (2.8 KB)
    10. Detect face and SWITCH ON the Device
    • 1. Switch on the device, if face is detected.mp4 (55.6 MB)
    • 1. Switch on the device, if face is detected.srt (2.7 KB)
    • 1.1 circuit diagram.jpg (239.2 KB)
    • 1.2 face_detection_iot.py (1.2 KB)
    • 1.3 Rpi3-pinout.png (68.9 KB)
    • 2. Demonstration - Switch on the device, if face is detected.mp4 (42.5 MB)
    • 2. Demonstration - Switch on the device, if face is detected.srt (3.6 KB)
    11. Acquiring data from Sensor and from Web Api
    • 1. Overview about Sensor and Web Api integration.mp4 (155.4 MB)
    • 1. Overview about Sensor and Web Api integration.srt (8.3 KB)
    • 2. Demonstration Program unit overview.mp4 (38.4 MB)
    • 2. Demonstration Program unit overview.srt (4.9 KB)
    • 2.1 sensordata-api.py (0.5 KB)
    • 3. Demonstration of Sensor, Web Api.mp4 (106.7 MB)
    • 3. Demonstration of Sensor, Web Api.srt (4.6 KB)
    12. Controlling IOT appliances through Adafruit web platform and through voice
    • 1. Web and voice control overview.mp4 (182.9 MB)
    • 1. Web and voice control overview.srt (10.2 KB)
    • 1.1 Adafruit library code install in Raspberry.html (0.1 KB)
    • 2. Adafruit MQTT setup, install Adafruit library and code unit discussion.mp4 (62.6 MB)
    • 2. Adafruit MQTT setup, install Adafruit library and code unit discussion.srt (7.7 KB)
    • 2.1 mqtt_sub.py (2.6 KB)
    • 3. Web control - Demonstration.mp4 (77.5 MB)
    • 3. Web control - Demonstration.srt (4.9 KB)
    • 4. Voice integration control overview.mp4 (76.5 MB)
    • 4. Voice integration control overview.srt (4.1 KB)
    • 5. IFTTT Setup - Interface between Google assistance and Adafruit MQTT feed.mp4 (34.6 MB)
    • 5. IFTTT Setup - Interface between Google assistance and Adafruit MQTT feed.srt (4.5 KB)
    • 6. Google Assistant - Install overview.mp4 (44.3 MB)
    • 6. Google Assistant - Install overview.srt (2.2 KB)
    • 7. Voice - web integrated control demonstration.mp4 (29.1 MB)
    • 7. Voice - web integrated control demonstration.srt (3.2 KB)
    13. Prototype - Building automation IOT using Open CV
    • 1. Integrated prototype overview.mp4 (58.9 MB)
    • 1. Integrated prototype overview.srt (6.2 KB)
    • 1.1 Case study - OPENCV - IOT.pdf (226.5 KB)
    • 2. Prototype - Building automation IOT using Open CV -Demonstration.mp4 (43.2 MB)
    • 2. Prototype - Building automation IOT using Open CV -Demonstration.srt (0.6 KB)
    14. ML - Supervisory learning - Identification of a person
    • 1. Identification of person - Supervisory learning- overview.mp4 (197.7 MB)
    • 1. Identification of person - Supervisory learning- overview.srt (10.2 KB)
    • 2. Walk through different program units.mp4 (57.4 MB)
    • 2. Walk through different program units.srt (6.4 KB)
    • 2.1 face_create_gray.py (2.4 KB)
    • 2.2 face_identifier.py (1.4 KB)
    • 2.3 face_trainer.py (1.3 KB)
    • 3. Demo - Face recognition program.mp4 (58.6 MB)
    • 3. Demo - Face recognition program.srt (3.4 KB)
    • 3.2 face_create_gray.py (2.4 KB)
    • 4. Demo - Creation of supervisory model for prediction.mp4 (50.1 MB)
    • 4. Demo - Creation of supervisory model for prediction.srt (2.4 KB)
    • 4.1 face_trainer.py (1.3 KB)
    • 5. Demo - Face identification using supervisory model created.mp4 (121.0 MB)
    • 5. Demo - Face identification using supervisory model created.srt (5.8 KB)
    • 5.1 face_identifier.py (1.4 KB)
    • DataSet
      • User.1.1.jpg (3.2 KB)
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      • User.1.11.jpg (5.8 KB)
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      • User.1.2.jpg (4.4 KB)
      • User.1.3.jpg (5.5 KB)
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      • User.1.5.jpg (4.1 KB)
      • User.1.6.jpg (6.0 KB)
      • User.1.7.jpg (5.0 KB)
      • User.1.8.jpg (4.1 KB)
      • User.1.9.jpg (3.3 KB)
      • User.2.1.jpg (6.8 KB)
      • User.2.2.jpg (10.9 KB)
      • User.2.3.jpg (3.2 KB)
      • User.2.4.jpg (4.8 KB)
      • User.2.5.jpg (3.4 KB)
      • User.2.6.jpg (3.0 KB)
      • User.2.7.jpg (3.0 KB)
      • User.2.8.jpg (2.7 KB)
      • User.2.9.jpg (4.1 KB)
      s1
      • images1.jpg (4.6 KB)
      • images10.jpg (6.6 KB)
      • images2.jpg (4.9 KB)
      • images3.jpg (5.0 KB)
      • images4.jpg (7.8 KB)
      • images5.jpg (6.6 KB)
      • images6.jpg (6.2 KB)
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      s2
      • images1.jpg (4.1 KB)
      • images10.jpg (6.7 KB)
      • images11.jpg (9.3 KB)
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      • images13.jpg (6.2 KB)
      • images2.jpg (6.6 KB)
      • images3.jpg (11.8 KB)
      • images4.jpg (7.6 KB)
      • images5.jpg (5.7 KB)
      • images6.jpg (7.5 KB)
      • images7.jpg (6.8 KB)
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      • images9.jpg (7.3 KB)
    • test1.jpg (13.3 KB)
    • test2.jpg (4.6 KB)
    • test3.jpg (7.5 KB)
    • 15. Bonus Lecture
      • 1. Bonus.mp4 (64.0 MB)
      • 1. Bonus.srt (3.2 KB)
      • 1.1 Data Modelling and Relational Database Design.html (0.1 KB)
      • 1.2 Google cloud - Firebase and Firestore nosql DB Introduction.html (0.2 KB)
      • 1.3 Internet of things (IOT) - Demystified.html (0.

Description

Machine learning - OpenCV based IOT using Raspberry pi



https://CourseWikia.com

MP4 | Video: h264, 1280x720 | 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.



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Udemy - Machine learning - OpenCV based IOT using Raspberry pi


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3.2 GB
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Udemy - Machine learning - OpenCV based IOT using Raspberry pi


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