Published in Analytics Vidhya·PinnedDeploy Machine Learning Web Applications with StreamlitAs a data scientist or machine learning engineer, it is not enough to leave your machine learning models in your notebooks. You will want your end-users to seamlessly interact with your model in a creative and easy way. Streamlit is a Python-based library that allows the creation and deployment of…Streamlit7 min readStreamlit7 min read
Published in MLearning.ai·Jul 28, 2022P-values in statistics simplified and the DataScience application.Pre-Requisite — Hypothesis and Hypothesis Test A hypothesis is an assumption about an expected association. Example: Increasing apple fruit consumption will result in a decreased frequency of visits to a doctor. Businesses that give customers loyalty points have more customer loyalty than businesses that don’t. In the research or statistics world, your objective is to determine…Data Science7 min readData Science7 min read
Published in MLearning.ai·Jun 10, 2022Evaluating classification models simplified.If you cannot measure it, you cannot improve it. ~ Lord Kelvin Any project that someone does can either be called a success or not. The machine learning world is no different either and we need a way to know when to stop and say our model is a success. IntroductionClassification Models8 min readClassification Models8 min read
Published in MLearning.ai·May 30, 2022Principal Component Analysis(PCA) SimplifiedLink to the code: Github Problem Statement Imagine you had a dataset with 1000 features. To visualize all these features and to try to explain the relationships between these features would be a nightmare. Moreover, your model runs the risk of Overfitting. …Pca8 min readPca8 min read
Published in MLearning.ai·May 21, 2022Handling Missing Values — Data ScienceDataSet and Notebook used in this article can be found here: Complete Notebook Link : Handling Missing Values DataSet Link: Melbourne Housing Dataset Introduction A perfect data set is usually a big win for any data scientist or machine learning engineer. Unfortunately, more often than not, datasets to be used to solve different data science use-cases will have missing data. …Data Science5 min readData Science5 min read
Published in Analytics Vidhya·May 17, 2022Understanding Naive Bayes AlgorithmNaive Bayes is a machine learning model used for classification. The Naive Bayes technique is based on probabilities. The probability of an event happening or not happening can be calculated using historical data. Let’s Dissect the meaning of Naive Bayes. It is called Naive because it is based on the Naive Assumption that each input variable is…Naive Bayes6 min readNaive Bayes6 min read
Published in MLearning.ai·Apr 30, 2022Understanding a Linear Regression Algorithm with Example.DataSet and Notebook used in this article can be found here: Complete Notebook Link: Multiple Linear Regression Model DataSet Link: Ecommerce Customers Let’s start on Linear Regression with a few scenarios: Finance companies predicting the top factors that cause a customer to default on a loan. Sports companies analyzing which variations of training have an effect on player performance. Factors affecting the economic growth of a country.Linear Regression10 min readLinear Regression10 min read
Apr 21, 2022Understanding AWS Glue for ETLIn the big data world, the biggest problem for many companies might be getting insights from data before it’s outdated. If you need to process the different types of data with speed, and efficiency to get the best value from the data, then you need to leverage ETL tools and…Aws Glue6 min readAws Glue6 min read
Feb 11, 2021Story Telling With Data — Data VisualizationAt the time of writing this article Google handles an average of 3.8 million searches per minute across the globe. That translates to 5.6 billion searches per day, or 2 trillion searches per year! When we look at Twitter there are 500 million tweets per day and around 200 billion…Data Visualization6 min readData Visualization6 min read
Published in Analytics Vidhya·Feb 9, 2021Deploy Machine Learning Model using Flask to Heroku — Beginners(Part 3)This tutorial is part 3 and the final part of the guide on how to deploy Machine Learn Models using Flask to Heroku via GitHub. The first part was a refresher on a logistic regression model on JupyterNotebook. The second part was on how to structure your flask application and…Heroku3 min readHeroku3 min read
