In this project, We are going to predict Medical insurance costs. We implemented Random Forest Regression using Python. The data has been downloaded from Kaggle website (medical insurance cost dataset) The data contains following columns: sex: insurance contractor gender, female, male bmi: Body mass index, providing an understanding of body, weights that are relatively high or low relative to height, objective index of body weight (kg / m ^ 2) using the ratio of height …
In this project, we aim to implement Time Series Forecasting using Prophet The data contains the following columns: lat : String variable, Latitude lng: String variable, Longitude desc: String variable, Description of the Emergency Call zip: String variable, Zipcode title: String variable, Title timeStamp: String variable, YYYY-MM-DD HH:MM:SS twp: String variable, Township addr: String variable, Address e: String variable, Dummy variable (always 1) . let’s get our environment ready with the libraries we’ll need and …
In this project, we aim to predict whether the message is spam or ham. we implemented Natural Language Processing, TF-IDF and SVM on Python. The data contains the following columns: Message: text message Category: Spam or Ham . let’s get our environment ready with the libraries we’ll need and then import the data! Check out the Data . Exploratory Data Analysis Let’s use describe by Category, this way we can begin to think about the …
One company prepared 10 great version of the same Ad. they are not very sure which Ad is suitable to put it on the social network. They want to put the Ad that will get the maximum clicks and lead to the best Conversion Rates. The company would like to hire a data scientist to find the best strategy to find out which version of the Ad is the best for the user and which …
You have a supermarket mall and through membership cards, you have some basic data about your customers like Customer ID, age, gender, annual income and spending score. Spending Score is something you assign to the customer based on your defined parameters like customer behavior and purchasing data. By the end of this case study, you would be able to answer the below questions. 1- How to achieve customer segmentation using Machine Learning algorithm (Hierarchical Clustering) …
In this project, we aim to predict whether a tumor is benign or malignant. we implemented KNN on Python. The data contains the following columns: BI_RADS_assessment: Definitely benign(1) to Highly suggestive of malignancy (5) Age: patient’s age in years Shape: mass shape: round=1 oval=2 lobular=3 irregular=4 (nominal) Margin: mass margin: circumscribed=1 microlobulated=2 obscured=3 ill-defined=4 spiculated=5 (nominal) Density: mass density high=1 iso=2 low=3 fat-containing=4 (ordinal) Severity: Predictor Class: benign=0 or malignant=1 . let’s get our environment …
In this project, we aim to predict whether or not it will rain tomorrow by training a Random Forest classification model on target RainTomorrow. This dataset contains daily weather observations from numerous Australian weather stations. The data contains the following columns: Date: The date of observation Location: The common name of the location of the weather station MinTemp: The minimum temperature in degrees celsius MaxTemp: The maximum temperature in degrees celsius Rainfall: The amount of rainfall recorded …
Logistic Regression is a Machine Learning classification algorithm that is used to predict the probability of a categorical dependent variable. In logistic regression, the dependent variable is a binary variable that contains data coded as 1 (yes, success, etc.) or 0 (no, failure, etc.). We use Logistic Regression To predict whether an email is spam (1) or not (0), Whether the tumor is malignant (1) or not (0), To predict whether a voice/face man (1) …