Implementing Gaussian Mixture Model using Expectation Maximization (EM) Algorithm in Python on IRIS dataset.
Implementing Frequent Pattern Growth Algorithm using Associative Rule learning to design book recommendation system in Python.
In this Packet, i am going to build and train a Deep Convolutional GAN (DCGAN) with Keras to generate images of digits.I am going to use mnist dataset.
In this project, there are multiple deep learning models which are able to identify Age, Gender, Emotion & Ethnicity of person present in the image.
For the ‘Iris’ dataset, I have create the Decision Tree classifier(in Python) and visualize it graphically.(Prediction using Decision Tree Algorithm)
Mobile Comparison System is a system which enables you to compare your desired smartphones.
Build an emotion and gender classifier for human oration with adequate accuracy trained via RAVDESS dataset using librosa
Estimate the maximum scour depth as a function of variables including flow depth and mean velocity, size of pier, median grain size and skew by using recorded weights via training data
Prediction of hand written digits value using CNN model trained via MNIST dataset using keras(tenserflow as the backend)
This project aims to build a simple real time face detector (video based) using two different approaches namely, Haar Cascades and face_recognition module in Python.
In this project I have built a model in Python with Keras which will detect whether a person has diabetes or not using certain features. Here is a simple ANN to detect diabetes using Keras.
This project is used to classify tweets on twitter whether they are related to a disaster or not based on the tweet contents. This Python project uses Keras framework and GloVe embedding.