Simple Data Engineering to Improve Your Machine Learning Results

So…data engineering again! Last week I participated in a Kaggle competition on Mechanisms of Action Prediction. (This competition is still on going, try it if you want!) Basically it asks you to train an algorithm to classify drugs based on their biological activity, and I want to share with you now some quite useful (and simple!) techniques to improve accuracy for tabular data I learned in this competition. Hope it helps!

Disclaimer: the following content is largely thanks to this amazing notebook. Make sure to check it for implementation details!

Rank Gauss

Various, numerous, and many machine learning techniques, such as PCA, actually rely on the assumption that the underlying data is normally distributed. With a dataset that is not normally distributed, the usefulness of such techniques will be negatively affected. RankGauss, a technique developed by Michael Jahrer in Porto Srguro’s Safe Driver Prediction, is a solution to such problem. I will not dive into the math behind it (because I am not good at Math!) but the purpose of RankGauss is to transform a non-normal distribution to a normal distribution, and it usually works better than standard standardization. Let us see the effect first!

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Simple Data Engineering to Improve Your Machine Learning Results

sophia tondon

1620898103

5 Latest Technology Trends of Machine Learning for 2021

Check out the 5 latest technologies of machine learning trends to boost business growth in 2021 by considering the best version of digital development tools. It is the right time to accelerate user experience by bringing advancement in their lifestyle.

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iOS App Dev

1620466520

Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

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Connor Mills

1659063683

HTML, CSS & JavaScript Project: Build Cocktail App

In this tutorial, we will learn how to create a cocktail app with HTML, CSS and Javascript.

Create a cocktail app where the user can search a cocktail of choice and the app displays the ingredients and instructions to make the cocktail. We use 'The Cocktail DB' API to fetch information required for our app.

Project Folder Structure:

Before we start coding let us take look at the project folder structure. We create a project folder called – ‘Cocktail App’. Inside this folder, we have three files. These files are index.html, style.css and script.js.

HTML:

We start with the HTML code. First, copy the code below and paste it into your HTML document.

<!DOCTYPE html>
<html lang="en">
  <head>
    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
    <title>Cocktail App</title>
    <!-- Google Font -->
    <link
      href="https://fonts.googleapis.com/css2?family=Poppins:wght@400;600&display=swap"
      rel="stylesheet"
    />
    <!-- Stylesheet -->
    <link rel="stylesheet" href="style.css" />
  </head>
  <body>
    <div class="container">
      <div class="search-container">
        <input
          type="text"
          placeholder="Type a cocktail name..."
          id="user-inp"
          value="margarita"
        />
        <button id="search-btn">Search</button>
      </div>
      <div id="result"></div>
    </div>
    <!-- Script -->
    <script src="script.js"></script>
  </body>
</html>

CSS:

Next, we style this app using CSS. For this copy, the code provided to you below and paste it into your stylesheet.

* {
  padding: 0;
  margin: 0;
  box-sizing: border-box;
  font-family: "Poppins", sans-serif;
}
body {
  height: 100vh;
  background: linear-gradient(#5372f0 50%, #000000 50%);
}
.container {
  position: absolute;
  transform: translate(-50%, -50%);
  top: 50%;
  left: 50%;
  width: 90vw;
  max-width: 37.5em;
  background-color: #ffffff;
  padding: 1.8em;
  border-radius: 0.6em;
  box-shadow: 0 1em 3em rgba(2, 9, 38, 0.25);
}
.search-container {
  display: grid;
  grid-template-columns: 9fr 3fr;
  gap: 1em;
  margin-bottom: 1.2em;
}
.search-container input {
  font-size: 1em;
  padding: 0.6em 0.3em;
  border: none;
  outline: none;
  color: #1f194c;
  border-bottom: 1.5px solid #1f194c;
}
.search-container input:focus {
  border-color: #5372f0;
}
.search-container button {
  font-size: 1em;
  border-radius: 2em;
  background-color: #5372f0;
  border: none;
  outline: none;
  color: #ffffff;
  cursor: pointer;
}
#result {
  color: #575a7b;
  line-height: 2em;
}
#result img {
  display: block;
  max-width: 12.5em;
  margin: auto;
}
#result h2 {
  font-size: 1.25em;
  margin: 0.8em 0 1.6em 0;
  text-align: center;
  text-transform: uppercase;
  font-weight: 600;
  letter-spacing: 0.05em;
  color: #1f194c;
  position: relative;
}
#result h2:before {
  content: "";
  position: absolute;
  width: 15%;
  height: 3px;
  background-color: #5372f0;
  left: 42.5%;
  bottom: -0.3em;
}
#result h3 {
  font-size: 1.1em;
  font-weight: 600;
  margin-bottom: 0.2em;
  color: #1f194c;
}
#result ul {
  margin-bottom: 1em;
  margin-left: 1.8em;
  display: grid;
  grid-template-columns: auto auto;
}
#result li {
  margin-bottom: 0.3em;
}
#result p {
  text-align: justify;
  font-weight: 400;
  font-size: 0.95em;
}
.msg {
  text-align: center;
}
@media screen and (max-width: 600px) {
  .container {
    font-size: 14px;
  }
}

Javascript:

Lastly, we implement the functionality using Javascript. Now copy the code below and paste it into your script file.

let result = document.getElementById("result");
let searchBtn = document.getElementById("search-btn");
let url = "https://thecocktaildb.com/api/json/v1/1/search.php?s=";
let getInfo = () => {
  let userInp = document.getElementById("user-inp").value;
  if (userInp.length == 0) {
    result.innerHTML = `<h3 class="msg">The input field cannot be empty</h3>`;
  } else {
    fetch(url + userInp)
      .then((response) => response.json())
      .then((data) => {
        document.getElementById("user-inp").value = "";
        console.log(data);
        console.log(data.drinks[0]);
        let myDrink = data.drinks[0];
        console.log(myDrink.strDrink);
        console.log(myDrink.strDrinkThumb);
        console.log(myDrink.strInstructions);
        let count = 1;
        let ingredients = [];
        for (let i in myDrink) {
          let ingredient = "";
          let measure = "";
          if (i.startsWith("strIngredient") && myDrink[i]) {
            ingredient = myDrink[i];
            if (myDrink[`strMeasure` + count]) {
              measure = myDrink[`strMeasure` + count];
            } else {
              measure = "";
            }
            count += 1;
            ingredients.push(`${measure} ${ingredient}`);
          }
        }
        console.log(ingredients);
        result.innerHTML = `
      <img src=${myDrink.strDrinkThumb}>
      <h2>${myDrink.strDrink}</h2>
      <h3>Ingredients:</h3>
      <ul class="ingredients"></ul>
      <h3>Instructions:</h3>
      <p>${myDrink.strInstructions}</p>
      `;
        let ingredientsCon = document.querySelector(".ingredients");
        ingredients.forEach((item) => {
          let listItem = document.createElement("li");
          listItem.innerText = item;
          ingredientsCon.appendChild(listItem);
        });
      })
      .catch(() => {
        result.innerHTML = `<h3 class="msg">Please enter a valid input</h3>`;
      });
  }
};
window.addEventListener("load", getInfo);
searchBtn.addEventListener("click", getInfo);

📁 Download Source Code: https://www.codingartistweb.com

#html #css #javascript

Nora Joy

1604154094

Hire Machine Learning Developers in India

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Services

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Nora Joy

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Applications of machine learning in different industry domains

Machine learning applications are a staple of modern business in this digital age as they allow them to perform tasks on a scale and scope previously impossible to accomplish.Businesses from different domains realize the importance of incorporating machine learning in business processes.Today this trending technology transforming almost every single industry ,business from different industry domains hire dedicated machine learning developers for skyrocket the business growth.Following are the applications of machine learning in different industry domains.

Transportation industry

Machine learning is one of the technologies that have already begun their promising marks in the transportation industry.Autonomous Vehicles,Smartphone Apps,Traffic Management Solutions,Law Enforcement,Passenger Transportation etc are the applications of AI and ML in the transportation industry.Following challenges in the transportation industry can be solved by machine learning and Artificial Intelligence.

ML and AI can offer high security in the transportation industry.
It offers high reliability of their services or vehicles.
The adoption of this technology in the transportation industry can increase the efficiency of the service.
In the transportation industry ML helps scientists and engineers come up with far more environmentally sustainable methods for powering and operating vehicles and machinery for travel and transport.

Healthcare industry

Technology-enabled smart healthcare is the latest trend in the healthcare industry. Different areas of healthcare, such as patient care, medical records, billing, alternative models of staffing, IP capitalization, smart healthcare, and administrative and supply cost reduction. Hire dedicated machine learning developers for any of the following applications.

Identifying Diseases and Diagnosis
Drug Discovery and Manufacturing
Medical Imaging Diagnosis
Personalized Medicine
Machine Learning-based Behavioral Modification
Smart Health Records
Clinical Trial and Research
Better Radiotherapy
Crowdsourced Data Collection
Outbreak Prediction

**
Finance industry**

In financial industries organizations like banks, fintech, regulators and insurance are Adopting machine learning to improve their facilities.Following are the use cases of machine learning in finance.

Fraud prevention
Risk management
Investment predictions
Customer service
Digital assistants
Marketing
Network security
Loan underwriting
Algorithmic trading
Process automation
Document interpretation
Content creation
Trade settlements
Money-laundering prevention
Custom machine learning solutions

Education industry

Education industry is one of the industries which is investing in machine learning as it offers more efficient and easierlearning.AdaptiveLearning,IncreasingEfficiency,Learning Analytics,Predictive Analytics,Personalized Learning,Evaluating Assessments etc are the applications of machine learning in the education industry.

Outsource your machine learning solution to India,India is the best outsourcing destination offering best in class high performing tasks at an affordable price.Business** hire dedicated machine learning developers in India for making your machine learning app idea into reality.
**
Future of machine learning
Continuous technological advances are bound to hit the field of machine learning, which will shape the future of machine learning as an intensively evolving language.

Improved Unsupervised Algorithms
Increased Adoption of Quantum Computing
Enhanced Personalization
Improved Cognitive Services
Rise of Robots

**Conclusion
**
Today most of the business from different industries are hire machine learning developers in India and achieve their business goals. This technology may have multiple applications, and, interestingly, it hasn’t even started yet but having taken such a massive leap, it also opens up so many possibilities in the existing business models in such a short period of time. There is no question that the increase of machine learning also brings the demand for mobile apps, so most companies and agencies employ Android developers and hire iOS developers to incorporate machine learning features into them.

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