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A list of premium posts for academy members containing hands-on tutorials, best practices, career advices and learning paths.

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PySpark - How to use Pandas User Defined Function (UDF)
Academy Membership PySparkPython

PySpark - How to use Pandas User Defined Function (UDF)

Introduction In the realm of big data processing, PySpark has emerged as a powerful tool for handling large-scale datasets. Its distributed computing framework allows for efficient processing of massive volumes of data. However, despite its capabilities, performing certain data transformations in PySpark can sometimes be cumbersome and complex. That'...

Type Hints in Python: A Guide for Beginners
Academy Membership Python

Type Hints in Python: A Guide for Beginners

Introduction As projects grow in size and complexity, it becomes increasingly important to ensure that code remains understandable and easy to work with. One powerful tool for achieving this is the use of type hints. In this tutorial, we will explain why and how to use type hints in Python....

Power BI - Import Data from XML file
Academy Membership Power BIBusiness Intelligence

Power BI - Import Data from XML file

Introduction The first step when creating a Power BI report is to connect with data sources. Power BI can connect to a wide range of data sources. This capability allows users to access and analyze data from various sources within Power BI. One important format to often deal with is...

Understanding the maths behind Long Short-Term Memory (LSTM) Networks: What happens inside an LSTM cell?
Academy Membership Deep Learning

Understanding the maths behind Long Short-Term Memory (LSTM) Networks: What happens inside an LSTM cell?

Introduction Traditional RNNs, limited by their simplistic structure, have problems retaining information over longer time periods, leading to the infamous vanishing gradient problem. Long Short-Term Memory (LSTM) Networks have the impressive ability to capture and preserve long-term dependencies in sequential data. But how is an LSTM able to do this?...

How to use Environment Variables in Python
Academy Membership Python

How to use Environment Variables in Python

Introduction Environment variables are used for securely storing and accessing sensitive data, facilitating seamless configuration management across different environments. In this tutorial, we will explore how to work with environment variables in Python. In order to do this, we will use the Python libraries os and python-dotenv. What is an...

Power BI - Custom Filtering in Power Query
Academy Membership Power BIBusiness Intelligence

Power BI - Custom Filtering in Power Query

Introduction Power BI offers with the Power Query Editor a powerful tool for cleaning and transforming data. One important part of data preparation is filtering your data. Filtering enables you to sort out irrelevant data and to reduce the amount of data. One important type of filtering is custom filtering....

PySpark - Window Functions
Academy Membership PythonPySpark

PySpark - Window Functions

Introduction Window functions in PySpark are a powerful feature for data manipulation and analysis. They allow you to perform complex calculations on subsets of data within a DataFrame, without the need for expensive joins or subqueries. In this tutorial, we will show you how to use window functions in PySpark....

Performance Metrics for Classification in Machine Learning: Understanding Accuracy, Precision, Recall and F1 Score
Academy Membership Machine Learning

Performance Metrics for Classification in Machine Learning: Understanding Accuracy, Precision, Recall and F1 Score

Introduction In Machine Learning, one essential step is evaluating the performance of a model. For classification models, the Confusion Matrix serves as a fundamental instrument for evaluating the performance. The Confusion Matrix provides a visualization of the results of a model. Based on the information from the Confusion Matrix, some...

How to containerize a FastAPI Application with Docker
Academy Membership FastAPIDocker

How to containerize a FastAPI Application with Docker

Introduction FastAPI, a high-performance Python web framework, coupled with Docker, a powerful containerization tool, can significantly boost the efficiency of your development workflow. In this blog post, we'll walk you through the process of setting up a FastAPI project using a Dockerfile, providing a flexible and scalable solution...

Confusion Matrix in Machine Learning: A Hands-On Explanation
Academy Membership Machine Learning

Confusion Matrix in Machine Learning: A Hands-On Explanation

Introduction In Machine Learning, one essential step is evaluating the performance of a model. For classification models, the Confusion Matrix serves as a fundamental instrument for evaluating the performance. It provides a clear and visual summary of the prediction accuracy of a model by illustrating the correspondence between the predicted...

PySpark - Add an ID Column to a DataFrame
Academy Membership PythonPySpark

PySpark - Add an ID Column to a DataFrame

Introduction One common task when working with large datasets is the need to generate unique identifiers for each record. In this tutorial, we will explore how to easily add an ID column to a PySpark DataFrame. In order to do this, we use the monotonically_increasing_id() function of PySpark....

A Beginner's Guide to Docker: Get Started with Containerization
Academy Membership Docker

A Beginner's Guide to Docker: Get Started with Containerization

Introduction In the fast-paced world of software development, efficiency and consistency are key. Docker, a powerful containerization platform, has revolutionized the way we build, ship, and run applications. In this tutorial, we show you how to get started with Docker. Step 1: Install Docker (if not already installed) First of...

Get started with PostgreSQL on Mac: A Step-by-Step Guide
Academy Membership PostgreSQL

Get started with PostgreSQL on Mac: A Step-by-Step Guide

Introduction PostgreSQL is one of the most widely used database management systems. One of the easiest ways to use PostgreSQL on macOS is the Postgres.app. Postgres.app provides a simple interface for setting up a server and a command-line interface (psql) for interacting with databases via the terminal. In...

Structured vs. Semi-structured vs. Unstructured Data
Academy Membership DataData Engineering

Structured vs. Semi-structured vs. Unstructured Data

Introduction Data comes in different forms, each with its own characteristics and challenges. Basically, there are three main categories of data: Structured, Semi-structured and Unstructured Data. In this tutorial, we explore the characteristics and some examples for each kind of data. Structured Data First, let's have a look...

How to set up a FastAPI Project
Academy Membership FastAPIPython

How to set up a FastAPI Project

Introduction FastAPI has quickly gained popularity as a modern, fast and easy-to-use Python web framework for building RESTful APIs. In this tutorial, we show you step-by-step how to set up a FastAPI project. Prerequisites First of all, make sure you have Python installed on your system. Furthermore, it is recommended...

How to use Power BI on Mac
Academy Membership Power BI

How to use Power BI on Mac

Introduction Power BI is one of the most widely used BI tools. But using Power BI on the Mac can be a challenge. This is because Microsoft does not offer a version of Power BI Desktop for the Mac. Nevertheless, there are workarounds for using Power BI on the Mac....

What is a Data Lakehouse?
Academy Membership Data EngineeringDatabricks

What is a Data Lakehouse?

Introduction In this tutorial, we want to explain the characteristics of a Data Lakehouse. In order to do this, we will take a closer look at the key features of Data Lakes and Data Warehouses and how a Data Lakehouse combines the best of both worlds. Definition At its core,...

PySpark - Explode Arrays into Rows of a DataFrame
Academy Membership PySparkPython

PySpark - Explode Arrays into Rows of a DataFrame

Introduction In this tutorial, we want to explode arrays into rows of a PySpark DataFrame. In order to do this, we use the explode() function and the explode_outer() function of PySpark. Import Libraries First, we import the following python modules: from pyspark.sql import SparkSession from pyspark.sql.functions...

Generative AI - Why now?

Generative AI - Why now?

Introduction In this tutorial, we want to explain why Generative AI (GenAI) is possible now. In order to do this, we describe the key factors that are responsible for the rise of Generative AI. Factors The key factors that enable Generative AI are availability of large datasets, computational power, and...

Deep Learning - How the McCulloch-Pitts Neuron works
Academy Membership Deep Learning

Deep Learning - How the McCulloch-Pitts Neuron works

Introduction In this tutorial we will cover the very first and the simplest mathematical neuron model in history - the McCulloch-Pitts Neuron. We look at the architecture and functionality. History The McCulloch-Pitts-Neuron is the simplest form of a neuron model and was published in 1943 by Warren McCulloch and Walter...

Keras - One-Hot Encoding
Academy Membership KerasPython

Keras - One-Hot Encoding

Introduction In this tutorial, we want to one-hot encode a NumPy array that contains categorical values. In order to do this, we use the to_categorical() function of Keras. Import Libraries First, we import the following python modules: import numpy as np from keras.utils import to_categorical Define Data...

Supervised vs. Unsupervised Learning

Supervised vs. Unsupervised Learning

Introduction Machine Learning can be divided into two main types: Supervised Learning and Unsupervised Learning. In this tutorial, we want to take a closer look to these approaches and compare them to each other. Overview Both supervised learning and unsupervised learning have their own characteristics and are suitable for solving...

Python - Import Stock Prices from Yahoo Finance
Academy Membership Python

Python - Import Stock Prices from Yahoo Finance

Introduction In this tutorial, we want to import Stock Prices from Yahoo Finance into Python. In order to do this, we use ticker module of YFinance. YFinance The python library yfinance enables access to financial data from Yahoo Finance. Yahoo Finance provides various financial market data such as stock...

What is Generative AI?

What is Generative AI?

Introduction In this tutorial, we want to explain Generative AI (GenAI). In order to do this, we describe both the terms Artificial Intelligence, Machine Learning, Deep Learning and Generative AI as well as the relationships between them. Overview First, we want to have a look to the relationships between Artificial...

PySpark - Regular Expressions (Regex)
Academy Membership PySparkPython

PySpark - Regular Expressions (Regex)

Introduction In this tutorial, we want to use regular expressions (regex) to filter, replace and extract strings of a PySpark DataFrame based on specific patterns. In order to do this, we use the rlike() method, the regexp_replace() function and the regexp_extract() function of PySpark. Import Libraries...

PySpark - User Defined Function (UDF)
Academy Membership PySparkPython

PySpark - User Defined Function (UDF)

Introduction In this tutorial, we want to create a UDF and apply it to a PySpark DataFrame. In order to do this, we will show you two different ways: using the udf() function and using the @udf decorator. Import Libraries First, we import the following python modules: from pyspark.sql...

PySpark - Aggregate Functions
Academy Membership PySparkPython

PySpark - Aggregate Functions

Introduction In this tutorial, we want to make aggregate operations on columns of a PySpark DataFrame. In order to do this, we use different aggregate functions of PySpark. Import Libraries First, we import the following python modules: from pyspark.sql import SparkSession from pyspark.sql.functions import * Create SparkSession Before...

PySpark - Concatenate DataFrames
Academy Membership PySparkPython

PySpark - Concatenate DataFrames

Introduction In this tutorial, we want to concatenate multiple PySpark DataFrames. In order to do this, we use the the union() method of PySpark. Import Libraries First, we import the following python modules: from pyspark.sql import SparkSession Create SparkSession Before we can work with Pyspark, we need to create...

PySpark - Join DataFrames
Academy Membership PySparkPython

PySpark - Join DataFrames

Introduction In this tutorial, we want to join PySpark DataFrames. In order to do this, we use the the join() method of PySpark. Import Libraries First, we import the following python modules: from pyspark.sql import SparkSession Create SparkSession Before we can work with Pyspark, we need to create a...

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