Searching for jobs has never been easy. But things were different until last year. Networking has always been important, but that used to happen face to face and it was easier to convince or convey your thoughts and ideas to people as to why you are a good fit for the respective roles.
Indexing Dataframes in Pandas
The complete blog on Medium : https://medium.com/@menonvid/eda-on-tanzania-water-pumps-efcbbde4ee9f
A neural network is a series of algorithms that endeavors to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates. In this sense, neural networks refer to systems of neurons, either organic or artificial in nature. Neural networks can adapt to changing input; so the network generates the best possible result without needing to redesign the output criteria.
Linear regression is a linear approach to modeling the relationship between a scalar response (or dependent variable) and one or more explanatory variables (or independent variables). The case of one explanatory variable is called simple linear regression. In linear regression, the relationships are modeled using linear predictor functions whose unknown model parameters are estimated from the data. Such models are called linear models. The conditional mean of the response given the values of the explanatory variables is assumed to be an affine function of those values; less commonly, the conditional median or some other quantile is used. Like all forms of regression analysis, linear regression focuses on the conditional probability distribution of the response given the values of the predictor.