Belajar dari contoh code Machine Learning yang paling sederhana dengan Python dan TensorFlow

Photo by Cookie the Pom on Unsplash


Sebelum terjun ke dunia coding, kita bisa menguji diri kita dengan soal matematika sederhana, seperti berikut.

x adalah input, dan y adalah outputJika x=5 maka y=11
Jika x=0 maka y=1
Jika x=-2 maka y=-3
Jika x=7 maka y= ... ?

Ketemu? Yes, = 15

Pertama yang kita lakukan adalah mempelajari tiga contoh yang ada. Kemudian otak kita akan mencoba mencari hubungan dari ketiga persamaan tersebut dan akhirnya menemukan polanya yaitu y = x * 2 + 1. …

The beginners guide to build a simple artificial neural networks model

Illustration of neural network
Illustration of neural network
Photo by Marius Masalar on Unsplash

Convolution neural networks (CNNs) is arguably the best machine learning model in computer vision tasks, but before we start learning CNNs it’s better to start with a simpler model.

In this article, we will use backpropagation as an artificial neural networks algorithm to classify MNIST handwritten digits and we will use TensorFlow as our machine learning library.

About the data

I think MNIST handwritten digits is the most popular data to experiment with deep learning. As written on Yann LeCun’s website:

It is a good database for people who want to try learning techniques and pattern recognition methods on real-world data while spending…

utilizing Visual Studio Code

Photo by Sigmund on Unsplash

There are cases when you have to change the annotation label from the image data that has already been annotated. Let’s say that we have annotated images with “cat”, and then we want to change that annotation to “kitten”.

Single image

Here’s how to change a single image annotation in Labelme. Right-click on the polygon labels list and then choose “Edit Label”, continue by typing a new name for the annotation.

Preparing data for Deep Learning

The Cats photo by Jari Hytönen on Unsplash

Maybe you have already made several image classification model. Utilizing datasets from Kaggle or the built-in dataset from TensorFlow and PyTorch. You can build your own datasets for image classification easily. But what about instance segmentation?


One of the tasks which need to be done before we can start training our instance segmentation model is to annotate the image data. In the image classification task, we only need to collect image data and separate them into folders according to their class.

Instance segmentation requires us to do an additional task, which is to annotate the object of interest. In this…

Muhammad Arnaldo

a Machine learning enthusiast. MS Student of Intelligent System > Machine Learning > Computer Vision.

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