Learn Test Driven Development (TDD) by Example

What is Test Driven Development?

TEST DRIVEN DEVELOPMENT (TDD) approach first, the test is developed which specifies and validates what the code will do. In simple terms, test cases are created before code is written. The purpose of TDD is to make the code clearer, simple and bug-free.

Test-Driven Development starts with designing and developing tests for every small functionality of an application. TDD instructs developers to write new code only if an automated test has failed. This avoids duplication of code. The full form of TDD is Test-driven development.

The simple concept of TDD is to write and correct the failed tests before writing new code (before development). This helps to avoid duplication of code as we write a small amount of code at a time in order to pass tests. (Tests are nothing but requirement conditions that we need to test to fulfill them).

Test-Driven development is a process of developing and running automated test before actual development of the application. Hence, TDD sometimes also called as Test First Development.

In this tutorial, you will learn more about-

• How to perform TDD Test
• TDD Vs. Traditional Testing
• What is acceptance TDD and Developer TDD
• Scaling TDD via Agile Model Driven Development (AMDD)
• Test Driven Development (TDD) Vs. Agile Model Driven Development (AMDD)
• Example of TDD
• Benefits of TDD

How to perform TDD Test

Following steps define how to perform TDD test,

1. Add a test.
2. Run all tests and see if any new test fails.
3. Write some code.
4. Run tests and Refactor code.
5. Repeat.

TDD cycle defines

1. Write a test
2. Make it run.
3. Change the code to make it right i.e. Refactor.
4. Repeat process.

Some clarifications about TDD:

• TDD is neither about “Testing” nor about “Design”.
• TDD does not mean "write some of the tests, then build a system that passes the tests.
• TDD does not mean “do lots of Testing.”

TDD Vs. Traditional Testing

TDD approach is primarily a specification technique. It ensures that your source code is thoroughly tested at confirmatory level.

• With traditional testing, a successful test finds one or more defects. It is same as TDD. When a test fails, you have made progress because you know that you need to resolve the problem.
• TDD ensures that your system actually meets requirements defined for it. It helps to build your confidence about your system.
• In TDD more focus is on production code that verifies whether testing will work properly. In traditional testing, more focus is on test case design. Whether the test will show the proper/improper execution of the application in order to fulfill requirements.
• In TDD, you achieve 100% coverage test. Every single line of code is tested, unlike traditional testing.
• The combination of both traditional testing and TDD leads to the importance of testing the system rather than perfection of the system.
• In Agile Modeling (AM), you should “test with a purpose”. You should know why you are testing something and what level its need to be tested.

What is acceptance TDD and Developer TDD

There are two levels of TDD

1. Acceptance TDD (ATDD): With ATDD you write a single acceptance test. This test fulfills the requirement of the specification or satisfies the behavior of the system. After that write just enough production/functionality code to fulfill that acceptance test. Acceptance test focuses on the overall behavior of the system. ATDD also was known as Behavioral Driven Development (BDD).
2. Developer TDD: With Developer TDD you write single developer test i.e. unit test and then just enough production code to fulfill that test. The unit test focuses on every small functionality of the system. Developer TDD is simply called as TDD.

The main goal of ATDD and TDD is to specify detailed, executable requirements for your solution on a just in time (JIT) basis. JIT means taking only those requirements in consideration that are needed in the system. So increase efficiency.

Scaling TDD via Agile Model Driven Development (AMDD)

TDD is very good at detailed specification and validation. It fails at thinking through bigger issues such as overall design, use of the system, or UI. AMDD addresses the Agile scaling issues that TDD does not.

Thus AMDD used for bigger issues.

The lifecycle of AMDD.

In Model-driven Development (MDD), extensive models are created before the source code is written. Which in turn have an agile approach?

In above figure, each box represents a development activity.

Envisioning is one of the TDD process of predicting/imagining tests which will be performed during the first week of the project. The main goal of envisioning is to identify the scope of the system and architecture of the system. High-level requirements and architecture modeling is done for successful envisioning.

It is the process where not a detailed specification of software/system is done but exploring the requirements of software/system which defines the overall strategy of the project.

1. Iteration 0: Envisioning

There are two main sub-activates.

1.1. Initial requirements envisioning.

It may take several days to identify high-level requirements and scope of the system. The main focus is to explore usage model, Initial domain model, and user interface model (UI).

1.2. Initial Architectural envisioning.

It also takes several days to identify architecture of the system. It allows setting technical directions for the project. The main focus is to explore technology diagrams, User Interface (UI) flow, domain models, and Change cases.

2. Iteration modeling:

Here team must plan the work that will be done for each iteration.

• Agile process is used for each iteration, i.e. during each iteration, new work item will be added with priority.
• First higher prioritized work will be taken into consideration. Work items added may be reprioritized or removed from items stack any time.
• The team discusses how they are going to implement each requirement. Modeling is used for this purpose.
• Modeling analysis and design is done for each requirement which is going to implement for that iteration.

3. Model storming:

This is also known as Just in time Modeling.

• Here modeling session involves a team of 2/3 members who discuss issues on paper or whiteboard.
• One team member will ask another to model with them. This modeling session will take approximately 5 to 10 minutes. Where team members gather together to share whiteboard/paper.
• They explore issues until they don’t find the main cause of the problem. Just in time, if one team member identifies the issue which he/she wants to resolve then he/she will take quick help of other team members.
• Other group members then explore the issue and then everyone continues on as before. It is also called as stand-up modeling or customer QA sessions.

4. Test Driven Development (TDD).

• It promotes confirmatory testing of your application code and detailed specification.
• Both acceptance test (detailed requirements) and developer tests (unit test) are inputs for TDD.
• TDD makes the code simpler and clear. It allows the developer to maintain less documentation.

5. Reviews.

• This is optional. It includes code inspections and model reviews.
• This can be done for each iteration or for the whole project.
• This is a good option to give feedback for the project.

Test Driven Development (TDD) Vs. Agile Model Driven Development (AMDD)

Example of TDD

Here in this example, we will define a class password. For this class, we will try to satisfy following conditions.

A condition for Password acceptance:

• The password should be between 5 to 10 characters.

First, we write the code that fulfills all the above requirements.

Scenario 1: To run the test, we create class PasswordValidator ();

We will run above class TestPassword ();

Output is PASSED as shown below;

Output:

Scenario 2: Here we can see in method TestPasswordLength () there is no need of creating an instance of class PasswordValidator. Instance means creating an object of class to refer the members (variables/methods) of that class.

We will remove class PasswordValidator pv = new PasswordValidator () from the code. We can call the isValid () method directly by PasswordValidator. IsValid (“Abc123”). (See image below)

So we Refactor (change code) as below:

Scenario 3: After refactoring the output shows failed status (see image below) this is because we have removed the instance. So there is no reference to non –static method isValid ().

So we need to change this method by adding “static” word before Boolean as public static boolean isValid (String password). Refactoring Class PasswordValidator () to remove above error to pass the test.

Output:

After making changes to class PassValidator () if we run the test then the output will be PASSED as shown below.

Advantages of TDD

• Early bug notification.

Developers test their code but in the database world, this often consists of manual tests or one-off scripts. Using TDD you build up, over time, a suite of automated tests that you and any other developer can rerun at will.

• Better Designed, cleaner and more extensible code.
  • It helps to understand how the code will be used and how it interacts with other modules.
  • It results in better design decision and more maintainable code.
  • TDD allows writing smaller code having single responsibility rather than monolithic procedures with multiple responsibilities. This makes the code simpler to understand.
  • TDD also forces to write only production code to pass tests based on user requirements.
• Confidence to Refactor
  • If you refactor code, there can be possibilities of breaks in the code. So having a set of automated tests you can fix those breaks before release. Proper warning will be given if breaks found when automated tests are used.
  • Using TDD, should results in faster, more extensible code with fewer bugs that can be updated with minimal risks.
• Good for teamwork

In the absence of any team member, other team members can easily pick up and work on the code. It also aids knowledge sharing, thereby making the team more effective overall.

• Good for Developers

Though developers have to spend more time in writing TDD test cases, it takes a lot less time for debugging and developing new features. You will write cleaner, less complicated code.

Summary:

• TDD stands for Test-driven development. It is a process of modifying the code in order to pass a test designed previously.
• It more emphasis on production code rather than test case design.
• Test-driven development is a process of modifying the code in order to pass a test designed previously.
• In Software Engineering, It is sometimes known as “Test First Development.”
• TDD includes refactoring a code i.e. changing/adding some amount of code to the existing code without affecting the behavior of the code.
• TDD when used, the code becomes clearer and simple to understand.

#testing #javascript #angular #reactjs #web-development

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TS-mockito: Mocking Library for TypeScript

TS-mockito

Mocking library for TypeScript inspired by http://mockito.org/

1.x to 2.x migration guide

1.x to 2.x migration guide

Main features

• Strongly typed
• IDE autocomplete
• Mock creation (mock) (also abstract classes) #example
• Spying on real objects (spy) #example
• Changing mock behavior (when) via:
  • thenReturn - return value #example
  • thenThrow - throw an error #example
  • thenCall - call custom method #example
  • thenResolve - resolve promise #example
  • thenReject - rejects promise #example
• Checking if methods were called with given arguments (verify)
  • anything, notNull, anyString, anyOfClass etc. - for more flexible comparision
  • once, twice, times, atLeast etc. - allows call count verification #example
  • calledBefore, calledAfter - allows call order verification #example
• Resetting mock (reset, resetCalls) #example, #example
• Capturing arguments passed to method (capture) #example
• Recording multiple behaviors #example
• Readable error messages (ex. 'Expected "convertNumberToString(strictEqual(3))" to be called 2 time(s). But has been called 1 time(s).')

Installation

npm install ts-mockito --save-dev

Usage

Basics

// Creating mock
let mockedFoo:Foo = mock(Foo);

// Getting instance from mock
let foo:Foo = instance(mockedFoo);

// Using instance in source code
foo.getBar(3);
foo.getBar(5);

// Explicit, readable verification
verify(mockedFoo.getBar(3)).called();
verify(mockedFoo.getBar(anything())).called();

Stubbing method calls

// Creating mock
let mockedFoo:Foo = mock(Foo);

// stub method before execution
when(mockedFoo.getBar(3)).thenReturn('three');

// Getting instance
let foo:Foo = instance(mockedFoo);

// prints three
console.log(foo.getBar(3));

// prints null, because "getBar(999)" was not stubbed
console.log(foo.getBar(999));

Stubbing getter value

// Creating mock
let mockedFoo:Foo = mock(Foo);

// stub getter before execution
when(mockedFoo.sampleGetter).thenReturn('three');

// Getting instance
let foo:Foo = instance(mockedFoo);

// prints three
console.log(foo.sampleGetter);

Stubbing property values that have no getters

Syntax is the same as with getter values.

Please note, that stubbing properties that don't have getters only works if Proxy object is available (ES6).

Call count verification

// Creating mock
let mockedFoo:Foo = mock(Foo);

// Getting instance
let foo:Foo = instance(mockedFoo);

// Some calls
foo.getBar(1);
foo.getBar(2);
foo.getBar(2);
foo.getBar(3);

// Call count verification
verify(mockedFoo.getBar(1)).once();               // was called with arg === 1 only once
verify(mockedFoo.getBar(2)).twice();              // was called with arg === 2 exactly two times
verify(mockedFoo.getBar(between(2, 3))).thrice(); // was called with arg between 2-3 exactly three times
verify(mockedFoo.getBar(anyNumber()).times(4);    // was called with any number arg exactly four times
verify(mockedFoo.getBar(2)).atLeast(2);           // was called with arg === 2 min two times
verify(mockedFoo.getBar(anything())).atMost(4);   // was called with any argument max four times
verify(mockedFoo.getBar(4)).never();              // was never called with arg === 4

Call order verification

// Creating mock
let mockedFoo:Foo = mock(Foo);
let mockedBar:Bar = mock(Bar);

// Getting instance
let foo:Foo = instance(mockedFoo);
let bar:Bar = instance(mockedBar);

// Some calls
foo.getBar(1);
bar.getFoo(2);

// Call order verification
verify(mockedFoo.getBar(1)).calledBefore(mockedBar.getFoo(2));    // foo.getBar(1) has been called before bar.getFoo(2)
verify(mockedBar.getFoo(2)).calledAfter(mockedFoo.getBar(1));    // bar.getFoo(2) has been called before foo.getBar(1)
verify(mockedFoo.getBar(1)).calledBefore(mockedBar.getFoo(999999));    // throws error (mockedBar.getFoo(999999) has never been called)

Throwing errors

let mockedFoo:Foo = mock(Foo);

when(mockedFoo.getBar(10)).thenThrow(new Error('fatal error'));

let foo:Foo = instance(mockedFoo);
try {
    foo.getBar(10);
} catch (error:Error) {
    console.log(error.message); // 'fatal error'
}

Custom function

You can also stub method with your own implementation

let mockedFoo:Foo = mock(Foo);
let foo:Foo = instance(mockedFoo);

when(mockedFoo.sumTwoNumbers(anyNumber(), anyNumber())).thenCall((arg1:number, arg2:number) => {
    return arg1 * arg2; 
});

// prints '50' because we've changed sum method implementation to multiply!
console.log(foo.sumTwoNumbers(5, 10));

Resolving / rejecting promises

You can also stub method to resolve / reject promise

let mockedFoo:Foo = mock(Foo);

when(mockedFoo.fetchData("a")).thenResolve({id: "a", value: "Hello world"});
when(mockedFoo.fetchData("b")).thenReject(new Error("b does not exist"));

Resetting mock calls

You can reset just mock call counter

// Creating mock
let mockedFoo:Foo = mock(Foo);

// Getting instance
let foo:Foo = instance(mockedFoo);

// Some calls
foo.getBar(1);
foo.getBar(1);
verify(mockedFoo.getBar(1)).twice();      // getBar with arg "1" has been called twice

// Reset mock
resetCalls(mockedFoo);

// Call count verification
verify(mockedFoo.getBar(1)).never();      // has never been called after reset

You can also reset calls of multiple mocks at once resetCalls(firstMock, secondMock, thirdMock)

Resetting mock

Or reset mock call counter with all stubs

// Creating mock
let mockedFoo:Foo = mock(Foo);
when(mockedFoo.getBar(1)).thenReturn("one").

// Getting instance
let foo:Foo = instance(mockedFoo);

// Some calls
console.log(foo.getBar(1));               // "one" - as defined in stub
console.log(foo.getBar(1));               // "one" - as defined in stub
verify(mockedFoo.getBar(1)).twice();      // getBar with arg "1" has been called twice

// Reset mock
reset(mockedFoo);

// Call count verification
verify(mockedFoo.getBar(1)).never();      // has never been called after reset
console.log(foo.getBar(1));               // null - previously added stub has been removed

You can also reset multiple mocks at once reset(firstMock, secondMock, thirdMock)

Capturing method arguments

let mockedFoo:Foo = mock(Foo);
let foo:Foo = instance(mockedFoo);

// Call method
foo.sumTwoNumbers(1, 2);

// Check first arg captor values
const [firstArg, secondArg] = capture(mockedFoo.sumTwoNumbers).last();
console.log(firstArg);    // prints 1
console.log(secondArg);    // prints 2

You can also get other calls using first(), second(), byCallIndex(3) and more...

Recording multiple behaviors

You can set multiple returning values for same matching values

const mockedFoo:Foo = mock(Foo);

when(mockedFoo.getBar(anyNumber())).thenReturn('one').thenReturn('two').thenReturn('three');

const foo:Foo = instance(mockedFoo);

console.log(foo.getBar(1));    // one
console.log(foo.getBar(1));    // two
console.log(foo.getBar(1));    // three
console.log(foo.getBar(1));    // three - last defined behavior will be repeated infinitely

Another example with specific values

let mockedFoo:Foo = mock(Foo);

when(mockedFoo.getBar(1)).thenReturn('one').thenReturn('another one');
when(mockedFoo.getBar(2)).thenReturn('two');

let foo:Foo = instance(mockedFoo);

console.log(foo.getBar(1));    // one
console.log(foo.getBar(2));    // two
console.log(foo.getBar(1));    // another one
console.log(foo.getBar(1));    // another one - this is last defined behavior for arg '1' so it will be repeated
console.log(foo.getBar(2));    // two
console.log(foo.getBar(2));    // two - this is last defined behavior for arg '2' so it will be repeated

Short notation:

const mockedFoo:Foo = mock(Foo);

// You can specify return values as multiple thenReturn args
when(mockedFoo.getBar(anyNumber())).thenReturn('one', 'two', 'three');

const foo:Foo = instance(mockedFoo);

console.log(foo.getBar(1));    // one
console.log(foo.getBar(1));    // two
console.log(foo.getBar(1));    // three
console.log(foo.getBar(1));    // three - last defined behavior will be repeated infinity

Possible errors:

const mockedFoo:Foo = mock(Foo);

// When multiple matchers, matches same result:
when(mockedFoo.getBar(anyNumber())).thenReturn('one');
when(mockedFoo.getBar(3)).thenReturn('one');

const foo:Foo = instance(mockedFoo);
foo.getBar(3); // MultipleMatchersMatchSameStubError will be thrown, two matchers match same method call

Mocking interfaces

You can mock interfaces too, just instead of passing type to mock function, set mock function generic type Mocking interfaces requires Proxy implementation

let mockedFoo:Foo = mock<FooInterface>(); // instead of mock(FooInterface)
const foo: SampleGeneric<FooInterface> = instance(mockedFoo);

Mocking types

You can mock abstract classes

const mockedFoo: SampleAbstractClass = mock(SampleAbstractClass);
const foo: SampleAbstractClass = instance(mockedFoo);

You can also mock generic classes, but note that generic type is just needed by mock type definition

const mockedFoo: SampleGeneric<SampleInterface> = mock(SampleGeneric);
const foo: SampleGeneric<SampleInterface> = instance(mockedFoo);

Spying on real objects

You can partially mock an existing instance:

const foo: Foo = new Foo();
const spiedFoo = spy(foo);

when(spiedFoo.getBar(3)).thenReturn('one');

console.log(foo.getBar(3)); // 'one'
console.log(foo.getBaz()); // call to a real method

You can spy on plain objects too:

const foo = { bar: () => 42 };
const spiedFoo = spy(foo);

foo.bar();

console.log(capture(spiedFoo.bar).last()); // [42] 

Thanks

• Szczepan Faber (https://www.linkedin.com/in/szczepiq)
• Sebastian Konkol (https://www.linkedin.com/in/sebastiankonkol)
• Clickmeeting (http://clickmeeting.com)
• Michał Stocki (https://github.com/michalstocki)
• Łukasz Bendykowski (https://github.com/viman)
• Andrey Ermakov (https://github.com/dreef3)
• Markus Ende (https://github.com/Markus-Ende)
• Thomas Hilzendegen (https://github.com/thomashilzendegen)
• Johan Blumenberg (https://github.com/johanblumenberg)

---

Download Details:

Author: NagRock
Source Code: https://github.com/NagRock/ts-mockito 
License: MIT license

#typescript #testing #mock 

Test Driven Development (TDD) with React Testing Library & Mock Service Worker

Let’s step up our testing game with two useful libraries that lend themselves excellently to a TDD approach.

Setting up

Whenever I want to try out something React-related, I use the library create-react-app. It gives you a ready-to-work-with basic React application with no configuration needed. Recent versions also come bundled with React Testing Library, so if you use the latest create-react-app, you can start using React Testing Library straight away. If not — install @testing-library/react and @testing-library/jest-dom in your existing React application.

I am going to implement the following functionality: a simple recipe list with a search function. It will look something like this to a user in a mobile browser:

Image credits: Burger Photo by Robin Stickel on Unsplash, French Toast Photo by Joseph Gonzalez on Unsplash, Salmon Photo by Casey Lee on Unsplash

Starting with a failing test

I want to use a TDD approach, so let’s start with a failing test. At this point, there is no component yet, so of course whatever test we write is going to fail. But let’s start small; I want a component named ‘Recipes’ that renders the expected heading text. Here is my test for that expectation:

	import React from 'react';
	import { render, screen } from '@testing-library/react';

	test('renders the heading', () => {
	  render(<Recipes />);

	  expect(screen.getByRole('heading')).toHaveTextContent('Recipe Finder');
	});

React testing library exports a render method, which will render a component and all of its child components. It also exports a screen object, holding a number of queries we can use to select different elements in our rendered component (and its child components too). The **getByRole **query lets me select the heading element and make an assertion on its text content.

Why select the heading element by its role and not for example a CSS class? The guiding principle of React Testing Library is “The more your tests resemble the way your software is used, the more confidence they can give you.” Therefore, we want to write our tests as close as possible to how the ultimate tester — the end user — will be using the application. Users don’t see CSS classes or data attributes; they interact with text, label text and semantic elements and roles. Using queries such as getByRole also encourages us to write accessible code, since these selectors are available to everyone, including users of screen readers.

Making the test pass

Our first test fails as expected.** Recipes is not defined.** But this is the first step in TDD — a failing test. Now, let’s make it pass by writing the simplest possible component with the correct heading and then importing it in our test file. Now, let’s re-run the test. It passes!

	import React from 'react';

	const Recipes = () => {
	  return (
	    <div>
	      <h1>Recipe Finder</h1>
	    </div>
	  )
	};

	export default Recipes;

Using further queries, we can make similar expectations for the input element and the “Find” button. The button also has a role, but for the input field, I will use the getByPlaceholderText query, since that is probably the closest query to how the user would find it on the page.

Start with a failing test…

	import React from 'react';
	import { render, screen } from '@testing-library/react';
	import Recipes from './Recipes';

	test('renders the heading, input field and button', () => {
	  render(<Recipes />);

	  expect(screen.getByRole('heading')).toHaveTextContent('Recipe Finder');
	  expect(screen.getByPlaceholderText('Enter an ingredient to find recipes...'))
	    .toBeInTheDocument();
	  expect(screen.getByRole('button')).toHaveTextContent('Find');
	});

… and implement the changes necessary to make it pass:

	import React from 'react';

	const Recipes = () => {
	  return (
	    <div>
	      <h1>Recipe Finder</h1>
	      <form>
	        <input 
	          type="text" 
	          name="ingredient"
	          placeholder="Enter an ingredient to find recipes..." 
	        />
	        <button type="submit">Find</button>
	      </form>
	    </div>
	  )
	};

	export default Recipes;

This way, we know what we expect from our code and more importantly — we will know if we break any functionality if the previously passing tests suddenly fail.

An important step in TDD is the refactor step, where we improve our code to for example make it easier to read, become more efficient and remove any duplication. The test should still pass after we refactor.

Setting up our mocks

When the application first renders, I want to display a list of all my recipes, just like in the visual design above. This requires some kind of communication with an API. We are going to use Mock Service Worker to mock the HTTP-requests, so that we can control the response data. Install Mock Service Worker with npm like this:

npm install msw --save-dev

With Mock Service Worker, we are not mocking a specific module (unlike if we were to use Jest.mock), which means that it makes no difference if I use fetch or a third-party library such as axios to get the data. This makes it incredibly flexible. Let’s add the following imports to our test file:

import { rest } from 'msw';
import { setupServer } from 'msw/node';

Here is how I set up mocking a call to the recipe list endpoint:

	import React from 'react';
	import { render, screen } from '@testing-library/react';
	import Recipes from './Recipes';
	import { rest } from 'msw';
	import { setupServer } from 'msw/node';

	const allRecipes = [
	  { id: 1, title: 'Burger' }, 
	  { id: 2, title: 'French toast' }, 
	  { id: 3, title: 'Salmon' }
	];

	const server = setupServer(
	  rest.get('/api/recipes', (req, res, ctx) => {
	    return res(ctx.json({ recipes: allRecipes }));
	  })
	);

	beforeAll(() => server.listen());

afterAll(() => server.close());

If you have worked with NodeJS and Express, the syntax looks very familiar. GET requests to ‘/api/recipes’ will respond with JSON containing the allRecipes array, just like a real API would. These two lines make sure the server starts listening (intercepting) before the tests run and closes its connection when the tests in this file have finished running:

beforeAll(() => server.listen());
afterAll(() => server.close());

#tdd #react-testing-library #react #test-driven-development #testing

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Hire Machine Learning Developer | Hire ML Experts in India

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

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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.
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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
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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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