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Deep Learning on ARM Processors 
18+ total hours of quality training
Complete source code included

Some Lesson Previews (2 of 99)

                                    Updating Parameters Effectively
                                    Coding : Updating our Model
 30 Day Money Back Guarantee
  •   Deep Learning on ARM Processors ($59.99 Value)
Total Value: $59.99
I personally guarantee that by the end of this training pack you will be able to accomplish the following
  • Build Neural Networks from scratch without libraries
  • ​Master quantization methods for deploying Neural Networks on microcontrollers
  • ​Build a Deep Learning Firmware for Handwriting Recognition

    Hardware requirements for this course ?

    • STM32F411-NUCLEO BOARD
    • ​STM32F429 -DISCO BOARD
    •  Setting Up Keil uVision 5
    • ​Download Keil uVision 5
    • ​Installing Keil uVision 5
    • ​Installing Packs
    • ​Changing the Compiler
    • ​Introduction
    • ​Introduction to Deep Learning
    • ​Considerations for Deep Learning on Microcontrollers
    • ​Coding : Setting Up a UART Driver
    • Further discussion on UART Alternate Function configuration
    • ​Building Blocks of Neural Networks
    • The Single Input Single Output Neural Network
    • ​Installing Tera Term
    • ​Coding : The Single Input Single Output Neural Network
    • ​The Multiple Input Single Output Neural Network
    • ​Coding : The Multiple Input Single Output Neural Network
    • ​Coding : Single Input Multiple Output Neural Network
    • ​The Multiple Input Multiple Output Neural Network
    • ​Coding : The Multiple Input - Multiple Output Neural Network
    • ​The Hidden Layer Neural Network
    • ​Coding : The Hidden Layer Neural Network
    • ​Comparing and Finding Error
    • ​Coding : Finding Error
    • ​Understanding data representation in Machine Learning
    • ​Understanding the "Learning" in Machine Learning
    • ​Coding : Brute-force Learning
    • ​Introduction to Gradient Descent
    • ​Functional Description of a Biological Neuron
    • ​Introduction to Neural Network (Part 2)
    • ​Case Study : Building a Neural Network to Predict Muscle Gain
    • ​Coding : Normalizing Datasets
    • ​Coding : Random Initialization of Weights
    • ​Understanding Activation Functions
    • ​Coding : Forward Propagation
    • ​Basics of Calculus
    •  CubeMX 5 & CubeIDE Primer
    • ​Downloading STM32CubeMX and CubeIDE
    • ​Installing STM32CubeMX and CubeIDE
    • ​Installing CubeMX Packages
    • ​Overview of CubeMX 5
    • ​CubeMX AI
    • ​Setting Up CubeMX.AI
    • ​Case Study : Deploying the MNIST Handwriting Recognition Model on ARM MCUs
    • ​Coding : Setting up our project
    • ​Coding : Cleaning Up our Project
    • ​Coding : Implementing the User Interface
    • ​Coding : Implementing the Touch Sensor
    • ​Coding : Scaling the Input Image
    • ​Coding : Deploying our Neural Network (Part 1)
    • ​Coding : Deploying our Neural Network (Part 2)
    • ​Coding : Updating our Model
    • ​CubeMX Primer
    • ​Setting Up STM32CubeMX
    • ​Overview of STM32CubeMX
    • ​Overview of STM32CubeMX (continued)
    • ​Checking for Updates and Firmwares
    • ​Pinout and Peripheral Configuration
    • ​Clock Tree configuration
    • ​The Configuration Tab
    • ​Input/Output
    • ​Input Interrupt
    • ​Basic Delay TIMER
    • ​Logistic Regression
    • ​Case Study : Building a Neural Network to Detect Cats
    • ​Deep Neural Networks
    • ​ Internals of a 2 layer Neural Network
    • ​Activation Functions
    • ​Understanding Computational Graphs
    • ​Updating Parameters Effectively
    • ​Understanding the Importance of Vectorization
    • ​Summary of Back-propagation and Forward-propagation
    • ​Initializing Parameters Effectively
    • ​Understanding Layers and Units
    • ​Understanding the Shapes
    • ​Understanding Broadcasting in Programming
    • ​Improving Neural Networks with Regularization Techniques
    • ​Overfitting and Underfitting
    • ​Building A Logistic Regression Model
    • ​Coding : Installing Python
    • Coding : Installing Python Packages
    • ​Coding : Setting up our project
    • ​Coding : Creating a Helper script
    • ​Coding : Inspecting our dataset
    • ​Coding : Inspecting the dataset Dimensions
    • ​Coding : Pre-processing our dataset
    • ​Coding : Implementing Forward and Backward Propagation
    • ​Coding : Implementing Gradient Descent
    • ​Coding : Implementing the Predictor function
    • ​Coding : Training our Model
    • ​Coding : Testing our Model
    • ​Building Deep Neural Networks From Scratch
    • ​Coding : Building A Deep Neural Network Library (Version 1)
    • ​Coding : Implementing a Two-Layer Neural Network (Inspecting the Dataset)
    • ​Coding : Implementing a Two-Layer Neural Network ( Pre-processing the Dataset)
    • ​Coding : Implementing a Two-Layer Neural Network ( Building the Model )
    • ​Coding : Implementing a Two-Layer Neural Network ( Testing the Model)
    • ​Coding : Building A Deep Neural Network Library (Version 2)
    • ​Coding : Implementing a Neural Network with an arbitrary number of Layers
    • ​Coding : Testing the Multi-Layer Neural Network
    • ​Convolutional Neural Networks (CNN)
    • ​Introduction to Convolution
    • ​Introduction to 2D Convolution
    • ​Describing ConvNet Layers
    • ​Understanding Padding
    • ​Understanding Striding
    • ​Convolution Over Volume
    • ​Single Layer of a Convolutional Neural Network
    • ​Examining a Complete Convolutional Neural Network
    • ​Understanding the Pooling Layer
    • ​Examining a Complete Convolutional Neural Network with a Pooling Layer
    • ​​Python Essentials
    • ​Downloading Python
    • ​Installing Python
    • ​Using IDLE
    • ​Installing Python packages
    • ​Testing the packages
    • ​Printing statements
    • ​Variables
    • ​Lists
    • ​Operators
    • ​Conditions
    • ​For Loops
    • ​While Loops
    • ​Functions
    • ​Dictionaries
    • ​Classes and Objects
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      • ​  Deep Learning on ARM Processors ($59.99 Value)
      Total Value: $59.99
      But today, you're getting all of this...
      For Only $29.78

       30 Day Money Back Guarantee

      Remember, I have no doubt you will love the training but should in case you are not completely satisfied you can request a refund within 30 days of purchase and you shall be fully refunded with no questions asked.

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      I know there are some websites out there that offer you something cool for a low price, but then stick you into some program that charges your card every month.
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      Thanks for taking the time to read this letter and I hope you enjoy the training!

      -Israel N Gbati