Practical ML/AI Guide for Businesses

  (the image was created using Visme [1]). Introduction Stock markets are analyzed either technically or fundamentally [2]. Fundamental analysis studies supply and demand relationships that define the stock price at any given time.  Technical analysis uses specialized methods of predicting prices by analyzing past price patterns and levels.  T here are many techniques used to examine stock price lines and patterns [2]: bar or high/low/close charts moving averages trend lines channels cycles resistance and support planes corrections double tops and bottoms head and shoulders formation trading volume open interest.  Theere are numerous limitations of these techniques: moving averages responds to general trends only is not highly precise short-term moving averages can give false indications, especially in times of volatile prices Trend lines work best with sustained trends positioning of trend lines is subjective and takes practice trends must be established before they become recognizabl

  Introduction This project is aimed to support ESC guidelines [1] that help health professionals manage people with heart failure (HF) according to the best available evidence.  The objective  is not only to develop an accurate survival   prediction model but also to discover essential factors for the survival  prediction of HF patients.   The complex nature of HF produces a significant  amount of information that is too difficult for clinicians to process as it  requires simultaneous consideration of multiple factors and their in teractions [2,3]. ML/AI techniques can  be utilized in this scenario to develop a reliable decision support system  to assist clinicians in properly interpreting the patients ’ records to make  informed decisions [2-5].  Workflow Let us install Anaconda IDE, upgrade pip and create a virtual environment Jupyter.  The Python-3 ML/AI workflow consists of the following steps:  Step 1: Install/import key libraries import numpy as np # linear algebra import pandas