Recommender Systems

What is Recommendation System : The recommendation systems are defined as a software tools to give suggestions for items to the users in which they might be interested. The suggestions might be related to decision-making processes which can be within these – what movie / TV series to watch, what playlist to listen, what items to buy, what news to read, or what videos to watch and many more in this list. The main objective …

Time Series Forecasting For Road Accidents in UK

In this project, We aim to Predict the number of future road accidents in the UK. The data has been published from the Department for Transport (GB)(Road Accident). This data provides detailed road safety data about the circumstances of personal injury road accidents in GB from 2014 to 2017. We are going to implement Time Series Forecasting using ARIMA & Prophet to find out the number of road accidents in the future. . What is Time …

Adult​ Census Income Analysis and Prediction

prediction of income

In this project, We aim to Predict whether income exceeds $50K/yr based on census data. The data has been downloaded from the UCI Repository website (Adult). We implemented the Artificial Neural Network (ANN) on Python to solve this problem. The data contains the following culumns: Age: continuous.  Workclass: Private, Self-emp-not-inc, Self-emp-inc, Federal-gov, Local-gov, State-gov, Without-pay, Never-worked.  fnlwgt: continuous.  Education: Bachelors, Some-college, 11th, HS-grad, Prof-school, Assoc-acdm, Assoc-voc, 9th, 7th-8th, 12th, Masters, 1st-4th, 10th, Doctorate, 5th-6th, Preschool.  Education-num: …

Prediction of Medical Insurance Cost

machine learning insurance medical

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 …

Prediction of Google Stocks Price

In this project, we are going to predict the stocks price of Alphabet Inc. The data contains the stocks price of Google from 2010 to 2019. This project will be implemented by Recurrent Neural Network and LSTM using Python. The data contains the following columns: Date Open High Low Close Volume . let’s get our environment ready with the libraries we’ll need and then import the data! Check out the Data Let’s extract the Open …

Time Series Forecasting for 911 Calls

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 …

Prediction of Aliens Vs. Predators

In this project, we will have some images of aliens and predators and by them, we will train a Convolutional Neural Network using Keras to predict if the image is an alien or predator. The Data contains the following folders:  train: 247 aliens and 247 predators validation: 100 aliens and 100 predators . Building CNN Let’s import the Keras libraries and packages. In this stage, we will initialise the CNN. Step 1: Create Convolutional Layer …

Prediction of Spam Messages

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 …

Prediction of Mobile Price

In this project, we used the sales data of mobile phones in various companies. The aim of this project is to find out the relation between features of a mobile phone(eg:- RAM, Internal Memory, etc) and selling price. In addition, predict the price range of the mobile. We are going to use Kernel Support Vector Machine, K-Fold Cross Validation and Grid Search to solve this problem. The data contains the following columns: battery_power: Total energy …