Finland postal code data including boundary coordinates

Data for all postal codes in Finland free of charge enriched by area boundaries as standard coordinates.

How to copy and paste text in Datalore terminal?

Datalore is an online data science environment. Typical CTRL+C and CTRL+V commands do not work in the Datalore terminal, so here is the solution.

List of business intelligence tools

List of business intelligence, reporting and data pipeline tools. Reporting tools Reporting and business intelligence tools.

Change Python version in Vertex AI

Vertex AI is a bare-bones analytics environment in Google Cloud.

Google Colab - Easily accessible Python workspace

Google Colab is a low barrier option to run Python scripts.

Datalore tech review

Datalore is a collaborative data science platform. The notebook experience has been taken to the next level.

Datalore pricing - Which licensing model to choose?

The online Python worskpace Datalore has three main models for pricing and licensing.

Wealth management web app - Technical implementation

Here is a presentation of the wealth management app I have developed.

Visualize postal code areas of Finland in Python

Reading and visualizing Finland’s postal code data on a map in Python.

Visualizing Finland's postal codes in a Filled map in Google Looker Studio

Visualize Finland’s postal code areas on a map in Google Looker Studio.

Shape Map visualization of Finland's postal codes in Power BI Desktop

with these instructions, you can visualize Finland’s postal code areas on a map in Power BI Desktop.

Public report in Looker Studio requires login - Instructions to solve

Looker Studio is a free reporting and business intelligence tool in Google Cloud.

Types of data science platforms - Workspace, MLOps or full stack?

Data Science platforms can be categorized to a few different buckets:

What kind of teams benefit from data science platforms?

Various kinds of teams from business innovation to academic research can benefit from data science platforms.

Value of data science platforms

Let’s go through the most typical use cases and their benefits to start using a data science platform.

List of data science platforms

Comprehensive list of data science platforms. Sometimes known also as machine learning platforms, ai platforms or DSML platforms.

ClearML - Robust MLOps platform for end-to-end solutions

Robust MLOps platform for end-to-end solutions. - Flexible Kubernetes deployments for advanced data science teams

For technically advanced teams looking for flexible Kubernetes deployments.

SmartPredict - Specific use cases with fully managed low code

Specific use cases with fully managed low code. - Experiment tracking platform for MLOps

Log experiments and ML models versions from any environment.

Paperspace Gradient - ML platform with their own data centers and IPU processors

Paperspace Gradient machine learning platform is best known from extensive GPU support.

Saturn Cloud - Data science workspace with Dask cluster

Saturn Cloud is a greate choice for data science teams who want to maximize flexibility of their environment.

Datalore - Introduction to the advanced analytics platform

Datalore is a fairly recent online platform for advanced data analytics.

Bodo is a faster alternative for Spark to run massive ETL jobs in Python

Bodo is a platform for data processing with Python and SQL.

Vertex AI User-Managed notebooks auto shutdown

User-Managed notebooks in Vertex AI are virtual workspaces for data exploration.

30 questions for Google Cloud Professional Machine Learning Engineer exam

Around 30 questions I memorize from the Google Cloud Professional Machine Learning certification exam.

I became a certified Google Cloud Professional Machine Learning Engineer!

After 4 months of intense studying I passed the Google Cloud certification for Professional Machine Learning Engineer!

MLOps in Google Cloud

Google Cloud Platform has excellent toolset to operationalize and productionize machine learning models.

Neural networks for natural language processing

Natural Language Processing (NLP) refers to tools and methods to explore text data as well as identifiy patterns and making predictions.

Neural networks for image recognition

Some notes about image recognition while preparing for Google Cloud MLE certification.

Keras for basic neural networks

Keras is one of the high level APIs in Tensorflow deep learning stack.

Tensorflow Extended (TFX) for MLOps

Tensorflow Extended (known as TFX) is a framework to define ML pipelines.

Tensorflow for ML Engineers

I have more experience from Pandas and Scikit-Learn Python libraries compared to Tensorflow.

Recommendation systems in Google Cloud

Recommendation systems are useful to personalize experience and find relevant items among huge catalogs.

Introduction to neural networks for ML

I heard about artificial neural networks first time around 2017. Since then I have tried to understand their behavior and explain them in a simple way.

Dataflow for ML Engineers in Google Cloud

Dataflow product in Google Cloud is mandatory for advanced data processing pipelines for machine learning solutions.

Machine learning fundamentals

Notes about fundamental ML concepts for Google Cloud ML Engineering certification.

Vertex AI for ML Engineers in Google Cloud

Some Google materials refer to it as Fully managed Tensorflow.

BigQuery for ML Engineers in Google Cloud

BigQuery is by far the most important storage and processing service in Google Cloud from ML perspective.

Machine learning products in Google Cloud

This is a summary of Google Cloud Platform (GCP) products relevant for Machine Learning Engineer role.

Running Flask frontend and backend in Kubernetes

Kubernetes have been everywhere lately. Especially in the context of MLOps. I gave it a try by creating web app with Python Flask.

Free data science workspaces

Google Colab, Databricks Community Edition, Visual Studio Code and Dcoker are some options to create a free data science workspace.

Comparison of machine learning platforms in major clouds

Comparing the major machine learning platforms AWS SageMaker, Azure Machine Learning, Google Vertex AI and Databricks.

What is a machine learning platform?

What is a machine learning platform? Introducing different components such as workbench, MLOps tools and cloud computation.

Machine learning in predictive maintenance

Machine learning in predictive maintenance. The two-part blog series provides insights for cost savings and an example script in Python.

Faking your geographical location to a web service - A hobby project

How to fool a web service about your actual location? In an experiment I pretended being in Ireland while traveling in Sweden.

Difference between data scientist and data engineer roles

In my opinion the big difference is that a data scientist focuses more on business problems while data engineer solves technical problems.

DataCamp - Learn data science online

Experiences from DataCamp online training. Structured data science courses are easy to organize for yourself or a team.

PySpark execution logic and code optimization

The article goes through the PySpark execution logic and provides guidelines to optimize the speed and performance.

Clustering data using SQL - An example with industrial IoT data

Clustering time series data with SQL - Nice 3D visualization using simple logic. Python notebook example in GitHub with industrial data.

Spark + Python tutorial for data developers

A tutorial for parallel computation with Spark and Python. The example has been ran on AWS cloud computing platform.

Introduction to AWS Glue for big data ETL

AWS Glue service works especially well for big data batch processing. Read the full post from

Finnish stemming and lemmatization in python

I wrote to Solita's blog about text analytics with the headline "Finnish stemming and lemmatization in python". The post has code examples.

Experiences from funding application classification by text analytics

Experiences from funding application classification by text analytics

Combining machine learning and business - Practical example

I give an example about machine learning use case in a format that should be understandable also for less technical people.

Maximizing uptime in Hiab hackathon

Read about Solita team's solution in a hackathon organized by Hiab. The task was to take advantage of data to maximize machine uptime.

Csv headers to list using Python

Python code to automatically list header fields of multiple CSV files. The original use case was related to data warehouse documentation.

Visualization and clustering of earthquake dataset

The built-in dataset quakes in RStudio had 1000 records of earthquakes nearby Fiji.

Virus problem - A statistical puzzle

The problem: A virus is spreading across the world - it kills without treatment. Your task is to solve a statistical puzzle.

Data science and business intelligence - Definitions

It's easy to spot these hype terms like data science, big data in LinkedIn or exhibition posters. I summarized the definitions.

Django tutorial - For data oriented web developers

Python based Django web framework offers a great platform to create a data oriented web application for any size of needs.