Rendezvous-with-Time-Series-Forecasting

Introduction

This Repository attempts to demonstrate modern Neural Networking tools to forecast Time Series data using Python.

Motivation

• In majority of the real-world problems it is difficult to estimate the seasonality of the data, gauge the trend or ensure stationarity.
• In traditional statistical approaches, it is essential to specify the assumptions of the model. For Instance, the right sort of trend(linear, non-linear, local or global)
• The ability of neural networks because of which we don't need to specify the relationship (linear, non-linear, seasonality, trend) that exist between input and output layer.

Dataset

• Google's historical stock prices are collected from the following NASDAQ link as a csv.