There are no reviews yet. Be the first to send feedback to the community and the maintainers!
Activity-Detection-using-IMU-sensor
User activity detection using IMU (Inertial Measurement Unit) sensors and power of deep learning. The accelerometer data from smart wearables is used for continuous activity detection, which can be used for in depth activity monitoring and recommender systems.Predict_RNA-RNA_Interaction
In this project I have used deep learning methods to predict RNA-RNA interaction (RRI) from the sequencing-based training data.Manufacturing_Line-i4.0
Shop floor always have challenges. When the part fails at the end of line testing, shop floor manager instinctively retrace your steps to identify at what point you went wrong. Here, the ML based algorithm is closely monitoring the parts as they progress through the manufacturing processes. So that the defective parts can be intelligently identified. An i4.0 use case with machine learning.Hierarchical-clustering
Correlation_Vapor-Pressure
Python-Coding-Interview
ANOVA---Sales-Volume
Analysis of VarianceLogistic-Regression
DCNN-timeseries-RUL
DCNN for Machine RUL Prediction using Time-series DataKNN_K-Nearest-Neighbor
k-nearest neighbors algorithm (k-NN) is a non-parametric method used for classification and regressionSupport-Vector-Regression-SVR-
NLP-GloVe-Sentiment_Analysis
Hypothesis-Testing---One-sample-t-test
Hypothesis Testing - One sample t testPython
Python learning, assignments, solutionsDescriptive_Statistics
Descriptive statistics fundamentalsCNN_MLP-cifar10
Here, we are going to classify images from the CIFAR-10 dataset. This covers preprocessing the imagees, training, validation and prediction using the convolutional neural networks model.Chi-Square-Test---Apparel-Company
Chi Square TestMLR-Case_Study-Housing_Marketing
Advanced-Python
Python basics for beginner and advancedRegression_Analysis
PCA-Visualization
Polynomial-Regression
Naive-Bayes-Classifier
Decision-Tree-Regression
Simple-Linear-Regression
Simple linear regression is a statistical method that allows us to summarize and study relationships between two continuous (quantitative) variablesDummy-Variables
K-Means-Clustering
Multiple-Linear-Regression
tflite-rock_paper_scissors
Two-sample-t-test
Random-Forest-Regression
A random forest is a meta estimator that fits a number of decision tree classifiers on various sub-samples of the dataset and uses averaging to improve the predictive accuracy and control over-fitting. The sub-sample size is always the same as the original input sample size but the samples are drawn with replacement if bootstrap=TrueANN-Churn_Modeling
A Predictive Churn Model is a tool that defines the steps and stages of customer churn, or a customer leaving your service or product. Having a predictive churn model gives you awareness and quantifiable metrics to fight against in your retention efforts.Random-Forest-Classification
Random forests or random decision forests are an ensemble learning method for classification, regression and other tasks that operates by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes or mean prediction of the individual trees.paired-t-test
PROJECT-EDA_Healthcare
The data at hand contains medical costs of people characterized by certain attributes. Explore and generate value out of this data.ANN-Bike_Sharing-Boston_Housing
Mini-Batch-K-Means-Clustering
Python-numpy
Market-Basket-Analysis
Decision-Tree-Classifier
Markdown-Pricing
normality-test
Time-Series-Analysis-ARIMA
Convolutional-Neural-Network-CNN
Predict_Price_from_Text-NLP-Tensorflow-Case_study
Wide Deep Learning - Wide models are models with sparse feature vectors, or vectors with mostly zero values. Multi-layer deep networks, on the other hand, where there may be unexpected relationships between inputs and outputs. If you have got a prediction task that could benefit from both of these models (recommendation models or models with text inputs are good examples), wide & deep might be a good fit.PROJECT---Face-Recognition-and-Blurring
Computer Vision Project: Blurring the face area of people from videos is done in all news channels and to hide the identity of a person. With computer vision, we can automatically detect the face region of the person and use it to blur the image. The project will be useful in blurring the faces of the people in the video.Predictive-Maintenace-Case_Study
Failure prediction is a major topic in predictive maintenance in many industries. Observing machine health and condition through sensor data is assumed to facilitate this type of maintenance by predicting Time-To-Failure (TTF) or Remaining Useful Life (RUL) of in-service equipment. This project aim to explore in this area.Typo-Corrector
Love Open Source and this site? Check out how you can help us