Univariate Stock Market Forecasting using Facebook Prophet in Python
Have you ever wondered how Facebook predicts the future? Meet Facebook Prophet, the open-source time series forecasting tool developed by … Read more
Supervised Learning
Supervised learning is a type of machine learning in which a model is trained on labeled data. This means that the training data includes both the input data and the corresponding correct output, and the goal of the model is to make predictions on new data that it has not seen before. In supervised learning, the model is able to learn from the training data by finding patterns and relationships between the input and the output, and then using this knowledge to make predictions on unseen data. Some common examples of supervised learning tasks include classification, regression, and sequence labeling. Supervised learning is a powerful and widely-used technique in the field of machine learning, and it has many applications in areas such as natural language processing, computer vision, and speech recognition. Examples of supervised learning algorithms include regression, naive Bayes, decision trees, decision forests, and support vector machines.
Create a Personalized Movie Recommendation Engine using Content-based Filtering in Python
Content-based recommender systems are a popular type of machine learning algorithm that recommends relevant articles based on what a user … Read more
Using Random Search to Tune the Hyperparameters of a Random Decision Forest with Python
Perfecting your machine learning model’s hyperparameters can often feel like hunting for a proverbial needle in a haystack. But with … Read more
Stock Market Forecasting Neural Networks for Multi-Output Regression in Python
Multi-output time series regression can forecast several steps of a time series at once. The number of neurons in the … Read more
Predictive Policing: Preventing Crime in San Francisco using XGBoost and Python
In this tutorial, we’ll be using machine learning to predict and map out crime in San Francisco. We’ll be working … Read more
Forecasting Beer Sales with ARIMA in Python
Time series analysis and forecasting is a tough nut to crack, but the ARIMA model has been cracking it for … Read more
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
Customer Churn Prediction – Understanding Models with Feature Permutation Importance using Python
Customer retention is a prime objective for service companies, and understanding the patterns that lead to customer churn can be … Read more
Tuning Model Hyperparameters with Grid Search at the Example of Training a Random Forest Classifier in Python
Are you struggling to find the best hyperparameters for your machine learning model? With Python’s Scikit-learn library, you can use … Read more
Mastering Multivariate Stock Market Prediction with Python: A Guide to Effective Feature Engineering Techniques
Are you interested in learning how multivariate forecasting models can enhance the accuracy of stock market predictions? Look no further! … Read more
Training a Sentiment Classifier with Naive Bayes and Logistic Regression in Python
Are you ready to learn about the exciting world of social media sentiment analysis using Python? In this article, we’ll … Read more