Using TensorFlow backend.
2018-10-31 19:07:29.243116: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
2018-10-31 19:07:29.494922: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1411] Found device 0 with properties:
name: TITAN V major: 7 minor: 0 memoryClockRate(GHz): 1.455
pciBusID: 0000:01:00.0
The library is useful for analyzing the emotions present in any audio file(call/music/recordings) into three classes namely positive, negative, neutral.
📘🐍🔍 Performed data analysis of news headlines by scraping websites and extracting metadata for each news headline using IBM's Watson NLU API. Explored data by plotting charts to uncover patterns and trends. Recorded all my findings in a Jupyter Notebook.
Emotion classification has always been a very challenging task in Computer Vision. Using the SSD object detection algorithm to extract the face in an image and using the FER 2013 released by Kaggle, this project couples a deep learning based face detector and an emotion classification DNN to classify the six/seven basic human emotions.
Using TensorFlow backend.
2018-10-31 19:07:29.243116: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
2018-10-31 19:07:29.494922: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1411] Found device 0 with properties:
name: TITAN V major: 7 minor: 0 memoryClockRate(GHz): 1.455
pciBusID: 0000:01:00.0