Analyzing the impact of weather on human sentiments
Omkar Deshpande (~omkar08) |
This talk focuses on demonstrating the power of Python's Statistical and Data Science Libraries. I have been working on a project to classify average human sentiments as positive or negative. Classification is completely based on the prediction made by the ML models, which incorporates the weather of the location. I will try to prove that weather is "one of the factor" contributing to the moods/emotions of humans and ultimately affects the decision making ability. I have achieved the accuracy of 60%, which is good enough, with the existing and publically available data. The accuracy will certainly grow along with the data.
- Basic knowledge of Python
- Basic understanding of Statistics
- Pinch of common sense
I am a Python enthusiast, always a keen explorer of the power of python. I have been passionate about Python since my early college days, and then I went on developing many Web Apps, APIs based on Django and Flask, later on, my journey with Python turned towards exploring the magic of Data Science. It has been quite an interesting time spent exploring this field, and I must say that the depth cannot be determined. The more you experience, the more moments of awe occur.