Fitting Support Vector Machines via Quadratic Programming
In this blog post we take a deep dive into the internals of Support Vector Machines. We derive a Linear SVM classifier, explain its advantages, and...
ML internals: Synthetic Minority Oversampling (SMOTE) Technique
In this article we discuss why fitting models on imbalanced datasets is problematic, and how class imbalance is typically addressed. We present the inner workings of...
Credit Card Fraud Detection using XGBoost, SMOTE, and threshold moving
In this article, we'll discuss the challenge organizations face around fraud detection, how machine learning can be used to identify and spot anomalies that the human...
On-Demand Spark clusters with GPU acceleration
Apache Spark has become the de facto standard for processing large amounts of stationary and streaming data in a distributed fashion. The addition of the MLlib...
How to supercharge data exploration with Pandas Profiling
Producing insights from raw data is a time-consuming process. Predictive modeling efforts rely on dataset profiles, whether consisting of summary statistics or descriptive charts. Pandas Profiling,...
Simplify data access and publish model results in Snowflake using Domino Data Lab
Introduction Arming data science teams with the access and capabilities needed to establish a two-way flow of information is one critical challenge many organizations face when...
PyCaret 2.2: Efficient Pipelines for Model Development
Data science is an exciting field, but it can be intimidating to get started, especially for those new to coding. Even for experienced developers and data...
Performing Non-Compartmental Analysis with Julia and Pumas AI
When analysing pharmacokinetic data to determine the degree of exposure of a drug and associated pharmacokinetic parameters (e.g., clearance, elimination half-life, maximum observed concentration ([latex]C_{max}[/latex]), time...
Density-Based Clustering
Original content by Manojit Nandi - Updated by Josh Poduska. Cluster Analysis is an important problem in data analysis. Data scientists use clustering to identify malfunctioning...
Bringing ML to Agriculture: Transforming a Millennia-old Industry
Guest post by Jeff Melching from The Climate Corporation At The Climate Corporation, we aim to help farmers better understand their operations and make better decisions...
The Curse of Dimensionality
Guest Post by Bill Shannon, Founder and Managing Partner of BioRankings Danger of Big Data Big data is the rage. This could be lots of rows...
Providing fine-grained, trusted access to enterprise datasets with Okera and Domino
Domino and Okera - Provide data scientists access to trusted datasets within reproducible and instantly provisioned computational environments. In the last few years, we’ve seen the...