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freecoders13

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Task#4 as an "IoT and Computer Vision" intern at THE SPARKS FOUNDATION. A real time Face Mask Detector using MobileNet, OpenCV, Tensorflow and keras, sklearn, Numpy, and Matplotlib. In this project, I've used transfer learning using 'imagenet' weights and further trained my model on DNN. I've implemented YOLO to make it a real time face mask detector using webcam.

Predict-Student-Score-Percentage-on-the-basis-of-Study-Hours.

A supervised Machine Learning model that predict student score percentage on the basis of study hours. The model uses Linear Regression to predict percentage score of a student. The linear regression is provided by Scikit-learn.

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Exploratory-Data-Analysis-on-World-Wide-Terrorism-Dataset.

Performed Exploratory Data Analysis on Terrorism Dataset to find useful information related to world wide terrorist attacks. Tools used are Python, Numpy, Pandas, Matplotlib, Seaborn and Plotly.

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Unsupervised-Machine-Learning-with-Iris-dataset.

Unsupervised Machine Learning model on Iris dataset using KMeans algorithm. Aim is to find opimum number of clusters for the dataset.

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Sentiment-Analysis-using-LSTM-and-GloVe-Embeddings

The model uses 50K movie reviews labelled as 'positive' and 'negative' that implements a Sentiment Analysis model using LSTM and GloVe(Global Vectors) Word Embeddings. There is 100-dimmensional GloVe(Global Vectors) word Embeddings is used. It is an unsupervised learning algorithm used for the similar representation of words having same meanings. LSTM(Long Short-term Memory) is a type of RNN model used for handling long sequence dependencies for classification task.

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