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praweshd / speech_emotion_recognition

Star 25

In this project, the performance of speech emotion recognition is compared between two methods (SVM vs Bi-LSTM RNN).Conventional classifiers that uses machine learning algorithms has been used for decades in recognizing emotions from speech. However, in recent years, deep learning methods have taken the center stage and have gained popularity fo…

machine-learning deep-neural-networks deep-learning recurrent-neural-networks speech-recognition svm-model svm-classifier lstm-neural-networks speech-analysis speech-emotion-recognition lstm-attention
  • Updated Jan 2, 2024
  • Jupyter Notebook

SinghAbhi1998 / Stock-Market-Price-Prediction

Star 13

Stock Market Price Prediction: Used machine learning algorithms such as Linear Regression, Logistics Regression, Naive Bayes, K Nearest Neighbor, Support Vector Machine, Decision Tree, and Random Forest to identify which algorithm gives better results. Used Neural Networks such as Auto ARIMA, Prophet(Time-Series), and LSTM(Long Term-Short Memory…

time-series random-forest linear-regression machine-learning-algorithms stock-price-prediction decision-trees naive-bayes-algorithm prophet svm-model lstm-neural-networks auto-arima logistics-regression
  • Updated Jul 18, 2020
  • Jupyter Notebook

Goutam1511 / Sign-Language-Recognition-using-Scikit-Learn-and-CNN

Star 13

The project aims at building a machine learning model that will be able to classify the various hand gestures used for fingerspelling in sign language. In this user independent model, classification machine learning algorithms are trained using a set of image data and testing is done. Various machine learning algorithms are applied on the datase…

machine-learning cnn artificial-intelligence artificial-neural-networks image-recognition python2 svm-learning svm-model svm-classifier cnn-for-visual-recognition cnn-classification
  • Updated Mar 18, 2018
  • Python
Classification-thanks-to-the-SVM-model-with-7-years-of-ozone-data-with-Machine-Learning

emirhanai / Classification-thanks-to-the-SVM-model-with-7-years-of-ozone-data-with-Machine-Learning

Star 10

I developed 2 machine learning software that predict and classify ozone day and non-ozone day. The working principle of the two is similar but there are differences. I got the dataset from ics.icu. Each software has a different mathematical model, Gaussian RBF and Linear Kernel, and classifications are visualized in different ways. I would be ha…

machine-learning ai svm machine-learning-algorithms artificial-intelligence machine-learning-library machinelearning machine-learning-coursera svm-model svm-classifier machine-learning-models machine-learning-tutorials yapay-zeka makine-ogrenmesi machine-learning-projects machine-learning-models-deployment
  • Updated Sep 6, 2021
  • Python

CatalystsReachOut / Diabetes-Prediction-Using-SVM

Star 10

In this case, we train our model with several medical informations such as the blood glucose level, insulin level of patients along with whether the person has diabetes or not so this act as labels whether that person is diabetic or non-diabetic so this will be label for this case.

python machine-learning deep-learning svm machine-learning-algorithms jupyter-notebook artificial-intelligence diabetes machinelearning standardization svm-model svm-classifier insulin blood-pressure diabetic-retinopathy-detection diabetes-detection diabetes-prediction diabetes-dateset-analysis
  • Updated Oct 9, 2022
  • Jupyter Notebook

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