Machine Learning merupakan metode yang dapat digunakan untuk menyelesaikan permasalahan dengan tingkat kesulitan yang kompleks. Metode ini sering dimanfaatkan untuk speech recognition, image classification, language translation.

Di dalam machine learning ada dua tahapan, yaitu tahapan training, dan deployment atau penggunaan model. Tahapan training merupakan tahapan dimana model mengalami proses learning. Algoritma akan mencari secara otomatis representasi input data yang terbaik dengan menggunakan error sebagai feedback. Secara ringkas, inilah tiga hal yang dibutuhkan untuk membuat machine learning model pada proses training


Documentation

Cloud Vision API is a Google Cloud service includes the capability to do Optical Character Recognition (OCR). This tutorial will show how to use Vision API on a GCP Notebook. First thing first, create a project on GCP. Sign up here for free and create a project if you don’t have any. Then navigate to this link, for further information related to Vision API. You can also try this feature on the web provided by Google here.

Here are the steps to use Vision API on a Notebook:
1. Enable the Vision API
2. Generate an API key
3. Upload the image…


#Serverless #Applied Machine Learning #GCP #BigQuery ML #DNN #TensorFlow #Keras

This article discusses an overview on how to build a machine learning model in a serverless manner with GCP. The brief explanation about machine learning concepts and how to implement it using BigQuery Machine Learning or TensorFlow and Keras are also will be covered here.

These following topics are covered in this article:

  1. Understand The Main Terms
  2. Build The Machine Learning Project
  3. Build a ML Model with BigQuery Machine Learning (BQML)
  4. Build a ML Model with TensorFlow and Keras

1. Understand The Main Terms

Thursy Satriani

Machine Learning Engineer at Cloud Ace

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