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: …
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 …
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 …
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 …
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 …