Wei WanginTowards Data Science·Mar 18, 2020Bayesian Optimization Concept Explained in Layman TermsBayesian Optimization for Dummies — Bayesian Optimization has been widely used for the hyperparameter tuning purpose in the Machine Learning world. Despite the fact that there are many terms and math formulas involved, the concept behind turns out to be very simple. …Machine Learning9 min readMachine Learning9 min read
Aman KrishnainPython in Plain English·Apr 7, 2022Kaggle Titanic Challenge: Features CreationBetter Data, Better Model! — Overview Hey folks, In the previous section of EDA, we looked at the distribution of different features. And their relationship with the prediction label, Survived, as well as among each other. We noticed that some of the features like Name contain extra information about a passenger’s title which can be useful…Machine Learning5 min readMachine Learning5 min read
Sparsh GuptainTowards Data Science·May 29, 2020Member-onlyInsightful Loan Default AnalysisVisualize Insights and Discover Driving Features in Lending Credit Risk Model for Loan Defaults — Lending Club is the largest online loan marketplace, facilitating personal loans, business loans, and financing of medical procedures. Borrowers can easily access lower interest rate loans through a fast online interface. Like most other lending companies, lending loans to ‘risky’ applicants is the largest source of financial loss (called credit…Data Science19 min readData Science19 min read
Sarah BeshrinTowards Data Science·Nov 2, 2020Member-onlyA Machine Learning Approach To Credit Risk AssessmentPredicting loan defaults and their probability — 1. Introduction Credit default risk is simply known as the possibility of a loss for a lender due to a borrower’s failure to repay a loan. Credit analysts are typically responsible for assessing this risk by thoroughly analyzing a borrower’s capability to repay a loan — but long gone are the days…Credit Risk10 min readCredit Risk10 min read
Suhas MaddaliinTowards Data Science·Sep 20, 2022Common Reasons why Machine Learning Projects FailUnderstanding various ways at which machine learning projects fail ensures that one takes the right steps and measures to avoid them before facing the situation — Okay, you did a good job in ensuring that your machine learning model is doing well on the training data. The next step would be to deploy it in real-time and get feedback from users and from the business about whether using it has led to an increase in the…Machine Learning7 min readMachine Learning7 min read
Lorraine LiinTowards Data Science·Feb 19, 2019How to Perform Exploratory Data Analysis with SeabornExploratory Data Analysis (EDA) is an approach to analyzing datasets to summarize their main characteristics. It is used to understand data, get some context regarding it, understand the variables and the relationships between them, and formulate hypotheses that could be useful when building predictive models. All data analysis must be…Data Science9 min readData Science9 min read
Destin GonginTowards Data Science·Mar 1, 2021Member-onlySemi-Automated Exploratory Data Analysis (EDA) in PythonComprehensive Data Exploration Process with One-Click — Exploratory Data Analysis, also known as EDA, has become an increasingly hot topic in data science. Just as the name suggests, it is the process of trial and error in an uncertain space, with the goal of finding insights. It usually happens at the early stage of the data science…Eda11 min readEda11 min read
ZitainTowards Data Science·Mar 7, 2022Member-only5 Effective Ways to Improve the Accuracy of Your Machine Learning ModelsHow to improve your models from 70% accuracy to over 90% — Creating machine learning models is a complex process that even the most experienced data scientists often make mistakes in. If you want your machine learning models to be as accurate as possible, you need to be aware of the ways that you can improve them. In this post, we will…Data Science5 min readData Science5 min read
Will KoehrseninTowards Data Science·Mar 3, 2018Beyond Accuracy: Precision and RecallChoosing the right metrics for classification tasks Would you believe someone who claimed to create a model entirely in their head to identify terrorists trying to board flights with greater than 99% accuracy? Well, here is the model: simply label every single person flying from a US airport as not…Machine Learning11 min readMachine Learning11 min read
