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Deep learning using Tensorflow Lite on Raspberry Pi
Type:
Other > Other
Files:
72
Size:
3.29 GiB (3528242008 Bytes)
Uploaded:
2022-09-18 04:11:31 GMT
By:
tuts756 Trusted
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1
Leechers:
4
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Info Hash:
65836B57FDE0DF3BB21D6DC5DF238BAA79CD1C1D




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Description

Course Workflow:

This course is focused on Embedded Deep learning in Python . Raspberry PI 4 is utilized as a main hardware and we will be building practical projects with custom data .

We will start with trigonometric functions approximation . In which we will generate random data and produce a model for Sin function approximation

Next is a calculator that takes images as input and builds up an equation and produces a result .This Computer vision based project is going to be using convolution network architecture for Categorical classification

Another amazing project is focused on convolution network but the data is custom voice recordings . We will involve a little bit of electronics to show the output by controlling our multiple LEDs using own voice .

Unique learning point in this course is Post Quantization applied on Tensor flow models trained on Google Colab . Reducing size of models to 3 times and increasing inferencing speed up to 0.03 sec per input .

Sections  :

    Non-Linear Function Approximation
    Visual Calculator
    Custom Voice Controlled Led

Outcomes After this Course : You can create

    Deep Learning Projects on Embedded Hardware
    Convert your models into Tensorflow Lite models
    Speed up Inferencing on embedded devices
    Post Quantization
    Custom Data for Ai Projects
    Hardware Optimized Neural Networks
    Computer Vision projects with OPENCV
    Deep Neural Networks with fast inferencing Speed

Hardware Requirements

    Raspberry PI 4
    12V Power Bank
    2 LEDs ( Red and Green )
    Jumper Wires
    Bread Board
    Raspberry PI Camera V2
    RPI 4 Fan
    3D printed Parts

Software Requirements

    Python3
    Motivated mind for a huge programming Project
    Before buying take a look into this course GitHub repository

Who this course is for:

    Developers
    Electrical Engineers
    Artificial Intelligence Enthusiasts

Requirements

    Basic Electronics Understanding
    Basic Python Programming
    Hardware : Raspberry pi 4
    Hardware : 12V Power Bank
    Hardware : Raspberry PI Camera V2
    Hardware : 2 LEDs ( Red and Green )
    Hardware : Bread Board
    Hardware : RPI 4 Fan
    Hardware : 3D printed Parts
    Hardware : Jumper Wires

Last Updated 9/2022

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[TutsNode.net] - Deep learning using Tensorflow Lite on Raspberry Pi/2. Visual Calculator/26. z.mp4191.98 MiB
TutsNode.net.txt63 B
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