In this project, we are going to make a Recurrent Neural Network for understanding the reviews of the users and extract the meaningful information behind them to figure out whether the user liked the movie or not. In the other words, the aim of this project is to classify the user movie reviews into positive and negative reviews. we are going to use Recurrent Neural Network using Keras to solve this problem . let’s get …
Month: August 2019
In this project, we are going to implement customer segmentation based on credit card usage behavior with two different approaches (K-means and Hierarchical Clustering) The data contains the following columns: CUST_ID : Identification of credit card holder (Categorical) BALANCE : Balance amount left in their account to make purchases BALANCE_FREQUENCY : How frequently the Balance is updated, score between 0 and 1 (1 = frequently updated, 0 = not frequently updated) PURCHASES : Amount of purchases made from account ONEOFF_PURCHASES : Maximum …
In this project, we will have some images of cats and dogs and by them, we will train a Convolutional Neural Network using Keras to predict if the image is a dog or cat. We have 10000 images in total in the dataset which divided to 8000 images for the training set and 2000 images for the test set. . Building CNN Let’s import the Keras libraries and packages. In this stage, we will initialise …
In this project, we aim to predict whether the customers will leave the bank or not?. We implemented the Artificial Neural Network (ANN) on Python. The data contains the following columns: RowNumber: The number of row CustomerId: Identity number Surname: Last Name CreditScore: The score of credit by bank Geography: Country or region Gender: Male or female Age: Customer age Tenure: Year in bank Balance: Amount in account NumOfProducts: How many accounts, bank account affiliated products …
Most of the Restaurants ask reviews to the customers and based on the reviews the restaurant can improve the customer satisfaction. So Reviews plays a vital role for the successful growth of the restaurant. The aim of this project is to predict whether the review is positive or negative. This project implemented by Natural Language Processing and Naive Bayes on Python. The dataset consists of 1000 rows and 2 columns. Review Column consist of customer …
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 …