Category: Machine Learning

Data Science, Machine Learning, Python Basics

Machine Learning with Python: Linear Regression

Introduction In this blog post, we’ll be exploring Linear Regression in Machine Learning with Python.  There are many potential applications for linear regression, especially for your business, including: Sales forecasting: Linear regression can be used to predict future sales based on historical data, such as product pricing, marketing expenses, and consumer demographics. Inventory management: Linear […]

Data Science, Machine Learning

7 Regression Algorithms Used in Python for Machine Learning

Regression analysis is a commonly used statistical technique for predicting the relationship between a dependent variable and one or more independent variables. In the field of machine learning, regression algorithms are used to make predictions about continuous variables, such as housing prices, student scores, or medical outcomes. Python, being one of the most widely used […]

Data Science, Machine Learning

Self Supervised Learning

Deep Learning without labels – Self-Supervised Learning¶ In this blog post we’ll discuss Self-Supervised Learning! Classical supervised learning suffers from four main problems: Fully labelled datasets are expensive or not available at all. There is a large amount of unlabeled datasets which cannot be leveraged by Supervised Learning. Difficuly in creating One-Shot or Few-Shot systems, […]

Machine Learning

How To Interpret The ROC Curve

The ROC curve is a valuable tool to measure the performance and then fine-tune classification models, as they show you the trade-off in sensitivity and specificity for a specific classifier at various thresholds. Despite this, some might find ROC curves difficult to understand. In this post, we’ll aim to eliminate this difficulty by providing a […]

Machine Learning

Understanding Random Forest Algorithm

The Random Forest algorithm is a machine learning technique that is used to predict the outcomes of events. It is a type of ensemble learning, which means that it combines the predictions of multiple models in order to produce a better prediction. A Random Forest algorithm is commonly used for classification and regression tasks. In […]

Data Science, Machine Learning

How to interpret box plots

Box plots are a great way to visualize your data. They can help you see the distribution of your data, as well as any outliers that may be present. In this article, we will show you how to interpret box plots, and give some examples of how they can be used in machine learning applications. […]

Data Science, Machine Learning

Understanding Boosted Trees Algorithms

There has been a recent resurgence of interest in Boosted Trees Algorithms. This is due to the success of machine learning algorithms in general, and the realization that boosted trees are a very powerful tool for solving many problems. In this article, we will discuss what boosted trees are, and how they work. We will […]