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In this machine learning project, we will be taking open source datasets that are publicly available and will be discussing various methods/techniques of performing time series forecasting. We will discuss about the traditional methods such as holt-winters method, Autoregressive integrated moving average method, exponential smoothing methods, as well we will also be comparing the modern methods of performing forecasting using neural network based models.
In this data science project, you will predict borrowers chance of defaulting on credit loans by building a credit score prediction model.
Build a predictive model to correctly classify products between 9 product categories (fashion, electronics, etc.) using the Otto Group dataset.
In this project, we are going to work on Deep Learning using H2O to predict Census income.