Recognizing Handwritten Digits with scikit-learn In this project we will try to recognize handwritten digits using machine learning models like support vector machine and random forest classifier with the help of scikit-learn library. Handwriting Recognition Handwritten text recognition is one of the most challenging task so to address this issue scikit-learn library plays important role to better understanding this technique. But people often think about OCR (Optical Character Recognition) software that can read text, pdf or other electronic documents. But this problem by choosing statistical approach may be optimal solution. You can read about scikit-learn library from this scikit-learn: mac...
In this blog or project we are going to analyze meteorological data, we will check trend of weather in past years, that how were remain those like wind speed, temperature, pressure, humidity, weather condition etc. Here we are going to use dataset of weatherHistory that is in excel format and analyze that, you can find this data from kaggle by this link ( https://www.kaggle.com/muthuj7/weather-dataset). This dataset contains hourly data of temperature and others from 2006 to 2016. This dataset corresponds to the country Finland of Northern Europe. To analyze this dataset first of all we have to import all necessary libraries like numpy, pandas, matplotlib, seaborn etc. like following way- import numpy as np import pandas as pd import seaborn as sns import matplotlib . pyplot as plt % matplotlib inline and after it we have to download dataset...
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