Tutorials

This page provides an overview of relataly tutorials for different main categories.

Classification

random search hyperparameter tuning a regression model python
Algorithms | Classification (two-class) | Cross-Validation | Finance | Hyperparameter Tuning | Machine Learning | Python | Random Decision Forests | Sales | Scikit-Learn | Seaborn | Use Cases

Using Random Search to Tune the Hyperparameters of a Random Decision Forest with Python

This article presents random search as an efficient method for automated hyperparameter tuning. Hyperparameters are model properties (e.g., the number … Read more

anomaly detection random isolation forests
Anomaly Detection | Classification (two-class) | Finance | Fraud Detection | K-Nearest Neighbors (KNN) | Local Outlier Factor | Python | Random Isolation Forest | Scikit-Learn | Seaborn

Multivariate Anomaly Detection on Time-Series Data in Python: Using Isolation Forests to Detect Credit Card Fraud

Credit card fraud has become one of the most common use cases for anomaly detection systems. The number of fraud … Read more

san Francisco crime map python
Algorithms | Classification (multi-class) | Crime Prevention | Decision Trees | Kaggle Competitions | Machine Learning | mplleaflet | Python | Random Decision Forests | Scikit-Learn | Seaborn

Crime Prevention in San Francisco using XGBoost and Python

This tutorial predicts crime types in San Francisco (SF) and plots them on a zoomable city map. We work with … Read more

image classification convolutional neural networks python tutorial
Classification (two-class) | Convolutional Neural Network (CNN) | Data Sources | Image Recognition | Keras | Neural Networks | Python | Tensorflow | Use Cases

Image Classification with Convolutional Neural Networks – Classifying Cats and Dogs in Python

This tutorial shows how to use Convolutional Neural Networks (CNNs) with Python for image classification. CNNs belong to the field … Read more

churn prediction python
Churn Prediction | Classification (two-class) | Data Science | Data Sources | Feature Permutation Importance | Hyperparameter Tuning | Machine Learning | Python | Random Decision Forests | Scikit-Learn | Seaborn | Use Cases

Customer Churn Prediction – Understanding Models with Feature Permutation Importance using Python

One of the primary goals of many service companies is to build solid and long-lasting relationships with their customers. Customers … Read more

hyperparameter tuning grid search python tutorial machine learning
Classification (two-class) | Hyperparameter Tuning | Logistics Use Cases | Machine Learning | Python | Random Decision Forests | Scikit-Learn | Seaborn

Tuning Model Hyperparameters with Grid Search at the Example of Training a Random Forest Classifier in Python

This article describes how to use the grid search technique with Python and Scikit-learn, to determine the optimum hyperparameters for … Read more

twitter sentiment analysis python
Algorithms | Classification (multi-class) | Logistic Regression | Machine Learning | Naive Bayes | Natural Language Processing | Python | Scikit-Learn | Seaborn | Sentiment Analysis

Sentiment Analysis with Naive Bayes and Logistic Regression in Python

In this article, we develop a Python classification model that analyzes Twitter comments’ sentiment. We will train different classification models … Read more

purchase intention prediction
Algorithms | Classification (two-class) | Data Science | Data Sources | Feature Permutation Importance | Kaggle Competitions | Logistic Regression | Machine Learning | Marketing Use Cases | Python | Sales | Scikit-Learn | Seaborn

Classifying Purchase Intentions of Online Shoppers with Python

Most online stores welcome countless visitors every day, but only a fraction of those visitors will make a purchase. Machine … Read more

Time-Series Forecasting

Affinity Propagation Time Series Clustering Stock market Prediction
Affinity Propagation (Clustering) | Cluster Analysis | Coinmarketcap API | Correlation | Covariance | Crypto Exchange APIs | Data Visualization | Finance | Python | Scikit-Learn | Seaborn | Stock Market Prediction | Time-Series-Forecasting

Clustering Financial Market Structures using Affinity Propagation in Python

Affinity propagation is an unsupervised clustering technique that stands out from other clustering approaches by its capacity to determine the … Read more

Finance | Keras | Neural Networks | Python | Recurrent Neural Networks | Scikit-Learn | Seaborn | Stock Market Prediction | Time-Series-Forecasting | Yahoo Finance API

Stock Market Prediction using Neural Networks for Multi-Output Regression in Python

In time series regression, the number of neurons in the final output layer determines how many steps in a time … Read more

feature engineering for stock market prediction, multivariate time series modelling
Algorithms | Finance | Keras | Machine Learning | Neural Networks | Python | Recurrent Neural Networks | Stock Market Prediction | Tensorflow | Time-Series-Forecasting | Use Cases | Yahoo Finance API

Feature Engineering for Multivariate Stock Market Prediction with Python

Multivariate forecasting models rely not exclusively on historical time series data but use additional features (multivariate = multiple input variables) … Read more

stock market prediction Python tutorial
Algorithms | Keras | Machine Learning | Neural Networks | Python | Recurrent Neural Networks | Stock Market Prediction | Tensorflow | Time-Series-Forecasting | Use Cases

Stock Market Prediction using Multivariate Time Series and Recurrent Neural Networks in Python

Regression models based on recurrent neural networks (RNN) can recognize patterns in time series data, making them an exciting technology … Read more

adjusting time series intervals python
Algorithms | Data Science | Keras | Neural Networks | Python | Recurrent Neural Networks | Synthetic Data | Tensorflow | Time-Series-Forecasting

Rolling Time Series Forecasting: Creating a Multi-Step Prediction for a Rising Sine Curve using Neural Networks in Python

We can solve many time forecasting problems by looking at a single step into the future. However, some forecasting problems … Read more

stock market prediction python
Algorithmic Trading | Algorithms | Finance | Keras | Neural Networks | Python | Recurrent Neural Networks | Stock Market Prediction | Tensorflow | Time-Series-Forecasting

Stock Market Prediction – Adjusting Time Series Prediction Intervals in Python

This tutorial shows how to adjust prediction intervals in time series forecasting using Keras recurrent neural networks and Python. We … Read more

Clustering

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Anomaly Detection

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Neural Networks

APIs

Distributed Computing

Author

  • Florian Follonier

    Hi, I am Florian, a Zurich-based consultant for AI and Data. Since the completion of my Ph.D. in 2017, I have been working on the design and implementation of ML use cases in the Swiss financial sector. I started this blog in 2020 with the goal in mind to share my experiences and create a place where you can find key concepts of machine learning and materials that will allow you to kick-start your own Python projects.