TinyML-edx

Introduction to Data Engineering Data engineering is a critical component of supervised learning, an

Keyword Spotting https://colab.research.google.com/github/tinyMLx/colabs/blob/master/3-5-13-Pretrain

Training Keyword Spotting in Colab The code for training your model in Colab is very similar to the

Spectrograms and MFCCs The raw analog audio signal is first transformed into a digital signal. You t

Keyword Spotting Application Architecture In this reading, we will go over the high-level architectu

Why are 8-Bits Enough for ML? When neural networks were first being developed, the biggest challenge

How to use TFLite models This will create a directory with a number of files and metadata describing

Sensors are important for machine learning applications as they act as a vehicle between algorithmic

Train your model with the new augmented data in order to overcome overfitting Dropout Regularization

Use complex images ## Download the neccessary data into the Colab Instance Define your model and opt

Introducing convolutions Let's explore how convolutions work by creating a basic convolution on a 2D

Fundamentals of TinyML: The Building Blocks of Deep Learning

I personally like to see it as a new paradigm for programming computers.