This repo houses a Jupyter Notebook which is intended to walk you through Gradient Descent Algorithm from scratch.

This project classifies network intrusions using machine learning models. It utilizes the CICIDS2017 dataset to detect various attack types. The model used in this project is implemented in a single Jupyter Notebook file instead of separate scripts.

Predicting the trend in the stock price is very complicated and challenging job as it depends on various factors or on different variables like economic conditions, investors’ expectations, and the political events. Because of the different variables, it is necessary to estimate the value of the product correctly and to obtain scoring income. One of the common subjects in the financial domain was stock-market prediction. A lot of mathematical models were employed before progressing in machine learning and artificial intelligence. While these models provided fairly accurate results, using these models was not effective and time consuming due to the rapidly evolving nature of the consumer. As a result of developments in machine learning and artificial intelligence, it has become possible to employ different models such as neural networks, regression, decision tree, Bayesian networks etc. Long Short-term Memory is used in this paper to predict the the stock price of the selected company. All the work and algorithm discussed in this paper will be done on Jupyter notebook which is free available Python based that enables quantitative analyst to prepare their own trading strategy.

🎬 🎞 🎥 This Jupyter notebook is is for a custom A.I tool (Photo Editor) that allows you to edit images using language instructions. Speeds up pre production workflows including storyboarding (previs), concept art, location scouting, costume and design etc. 🤖 💭