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detect-parkinsons-disease
Parkinson disease is associated with movement disorder symptoms, such as tremor, rigidity, bradykinesia, and postural instability. The manifestation of bradykinesia and rigidity is often in the early stages of the disease. These have a noticeable effect on the handwriting and sketching abilities of patients, and micrographia has been used for early-stage diagnosis of Parkinson’s disease. While handwriting of a person is influenced by a number of factors such as language proficiency and education, sketching of a shape such as the spiral has been found to be non-invasive and independent measure.lstm-time-series-prediction-pytorch
Long Short Term Memory unit (LSTM) was typically created to overcome the limitations of a Recurrent neural network (RNN). The Typical long data sets of Time series can actually be a time-consuming process which could typically slow down the training time of RNN architecture. We could restrict the data volume but this a loss of information. And in any time-series data sets, there is a need to know the previous trends and the seasonality of data of the overall data set to make the right predictions.python-outlier-detection
The performance of the machine learning algorithm also depends on properly detecting outliers in the dataset. Particularly the regression algorithms are very easily influenced by the outliers. In this case, if the dataset is not correctly cleaned by removing the outlier, then the model performance is unlikely to be as expected. PyOD - Python Toolkit for detecting Outliers. This package contains about 20 algorithms for detecting outliers.crime-data-visualization-and-analysis
Data_Science
Principle Component Analysis and Text Mining With Ropenvino-people-counter
The people counter application is one of a series of IoT reference implementations aimed at instructing users on how to develop a working solution for a particular problem. It demonstrates how to create a smart video IoT solution using Intel® hardware and software tools. This solution detects people in a designated area, providing the number of people in the frame, average duration of people in frame, and total count.image-anomaly-detecton
In Machine Learning, anomaly detection (outlier detection) is the identification of rare items, events or observations which raise suspicions by differing significantly from the majority of the data. Typically the anomalous items will translate to some kind of problem such as bank fraud, a structural defect, medical problems or errors in a text. Anomalies are also referred to as outliers, novelties, noise, deviations and exceptions.sentiment-analysis-sagemaker-deployment
In this project we will construct a recurrent neural network for the purpose of determining the sentiment of a movie review using the IMDB data set. we will create this model using Amazon's SageMaker service. In addition, we will deploy our model and construct a simple web app which will interact with the deployed model.Love Open Source and this site? Check out how you can help us