The most significant change since the Industrial Revolution

The use of Artificial Intelligence (AI) in Industry 4.0 has been baking for quite a while, but technology is now ripe enough to turn it into reality. It involves the infusion of data and smart automation within the manufacturing process together with human input. To do so, it makes use of various technologies such as the Internet of Things, Cloud Computing, Blockchain and others. Let us try for a second to understand why the use of AI is important.

If you are the owner of a manufacturing plant, then you’re probably familiar with having various machines working in tandem and producing thousands of devices every day. Monitoring the different processes which go on simultaneously is already a huge headache. Most probably, you are at the mercy of the various operators in order to ensure that the level of production is at least maintained. However, even though you are taking the best possible measures to mitigate any risks and ensure that everything runs smoothly, things still go wrong. When they do, havoc breaks loose until the main issues are sorted out. Things get further complicated when problems arise during a weekend or a public holiday since the availability of skilled professionals is very limited and costly. When production is halted, it obviously results in financial losses which might also impact production deadlines. Large production processes would normally depend on warehouses of raw materials, parts or other items. All of these cost a lot of money and involve huge risks if they are mismanaged. The handling of these assets alone is already a huge headache for management. And we haven’t even started considering how to improve the plant; maybe through optimisation or changing the basic configuration. But sometimes, when dealing with legacy systems, any change can be catastrophic and as such, management might be slow to respond towards the changing needs of the market. Sometimes, it is simply too late and the lack of decisive action leads the plant towards certain doom.

Do these scenarios sound too familiar? Well, the good thing is that most of them can be handled quite easily with today’s technologies. To understand what we mean, let us give you some examples.

#machine-learning #digital-transformation #industry-4-0 #artificial-intelligence #industry #deep learning

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The most significant change since the Industrial Revolution

The use of Artificial Intelligence (AI) in Industry 4.0 has been baking for quite a while, but technology is now ripe enough to turn it into reality. It involves the infusion of data and smart automation within the manufacturing process together with human input. To do so, it makes use of various technologies such as the Internet of Things, Cloud Computing, Blockchain and others. Let us try for a second to understand why the use of AI is important.

If you are the owner of a manufacturing plant, then you’re probably familiar with having various machines working in tandem and producing thousands of devices every day. Monitoring the different processes which go on simultaneously is already a huge headache. Most probably, you are at the mercy of the various operators in order to ensure that the level of production is at least maintained. However, even though you are taking the best possible measures to mitigate any risks and ensure that everything runs smoothly, things still go wrong. When they do, havoc breaks loose until the main issues are sorted out. Things get further complicated when problems arise during a weekend or a public holiday since the availability of skilled professionals is very limited and costly. When production is halted, it obviously results in financial losses which might also impact production deadlines. Large production processes would normally depend on warehouses of raw materials, parts or other items. All of these cost a lot of money and involve huge risks if they are mismanaged. The handling of these assets alone is already a huge headache for management. And we haven’t even started considering how to improve the plant; maybe through optimisation or changing the basic configuration. But sometimes, when dealing with legacy systems, any change can be catastrophic and as such, management might be slow to respond towards the changing needs of the market. Sometimes, it is simply too late and the lack of decisive action leads the plant towards certain doom.

Do these scenarios sound too familiar? Well, the good thing is that most of them can be handled quite easily with today’s technologies. To understand what we mean, let us give you some examples.

#machine-learning #digital-transformation #industry-4-0 #artificial-intelligence #industry #deep learning

Data industry is changing the face of our World: True or False?

The data industry is booming as we continue to produce data in greater quantities and on a massive scale.

Regardless of the sector you work in or irrespective of your preferences, you will certainly find out how “data” is transforming our world’s image. It could be part of a research that helps cure a disease, increase the profit of a company, make a construction more convenient, or be accountable for those targeted advertisements you keep seeing. The data industry is booming as we continue to produce data in greater quantities and on a massive scale.

Data Industry

Different types of employment in the data industry

#big data #latest news #data industry #data industry is changing the face of our world #data industry #world

What is Industry 4.0?Latest Trends, Technologies & Examples

https://www.mobinius.com/blogs/what-is-industry-4-0-trends-technologies-examples

#industrial revolution 4.0 #digital transformation companies #industry 4.0 services #industry 4. 0 technologies #internet of things #iot applications

Exploring Mutable and Immutable in Python

In this Python article, let's learn about Mutable and Immutable in Python. 

Mutable and Immutable in Python

Mutable is a fancy way of saying that the internal state of the object is changed/mutated. So, the simplest definition is: An object whose internal state can be changed is mutable. On the other hand, immutable doesn’t allow any change in the object once it has been created.

Both of these states are integral to Python data structure. If you want to become more knowledgeable in the entire Python Data Structure, take this free course which covers multiple data structures in Python including tuple data structure which is immutable. You will also receive a certificate on completion which is sure to add value to your portfolio.

Mutable Definition

Mutable is when something is changeable or has the ability to change. In Python, ‘mutable’ is the ability of objects to change their values. These are often the objects that store a collection of data.

Immutable Definition

Immutable is the when no change is possible over time. In Python, if the value of an object cannot be changed over time, then it is known as immutable. Once created, the value of these objects is permanent.

List of Mutable and Immutable objects

Objects of built-in type that are mutable are:

• Lists
• Sets
• Dictionaries
• User-Defined Classes (It purely depends upon the user to define the characteristics) 

Objects of built-in type that are immutable are:

• Numbers (Integer, Rational, Float, Decimal, Complex & Booleans)
• Strings
• Tuples
• Frozen Sets
• User-Defined Classes (It purely depends upon the user to define the characteristics)

Object mutability is one of the characteristics that makes Python a dynamically typed language. Though Mutable and Immutable in Python is a very basic concept, it can at times be a little confusing due to the intransitive nature of immutability.

Objects in Python

In Python, everything is treated as an object. Every object has these three attributes:

• Identity – This refers to the address that the object refers to in the computer’s memory.
• Type – This refers to the kind of object that is created. For example- integer, list, string etc. 
• Value – This refers to the value stored by the object. For example – List=[1,2,3] would hold the numbers 1,2 and 3

While ID and Type cannot be changed once it’s created, values can be changed for Mutable objects.

Check out this free python certificate course to get started with Python.

Mutable Objects in Python

I believe, rather than diving deep into the theory aspects of mutable and immutable in Python, a simple code would be the best way to depict what it means in Python. Hence, let us discuss the below code step-by-step:

#Creating a list which contains name of Indian cities  

cities = [‘Delhi’, ‘Mumbai’, ‘Kolkata’]

# Printing the elements from the list cities, separated by a comma & space

for city in cities:
		print(city, end=’, ’)

Output [1]: Delhi, Mumbai, Kolkata

#Printing the location of the object created in the memory address in hexadecimal format

print(hex(id(cities)))

Output [2]: 0x1691d7de8c8

#Adding a new city to the list cities

cities.append(‘Chennai’)

#Printing the elements from the list cities, separated by a comma & space 

for city in cities:
	print(city, end=’, ’)

Output [3]: Delhi, Mumbai, Kolkata, Chennai

#Printing the location of the object created in the memory address in hexadecimal format

print(hex(id(cities)))

Output [4]: 0x1691d7de8c8

The above example shows us that we were able to change the internal state of the object ‘cities’ by adding one more city ‘Chennai’ to it, yet, the memory address of the object did not change. This confirms that we did not create a new object, rather, the same object was changed or mutated. Hence, we can say that the object which is a type of list with reference variable name ‘cities’ is a MUTABLE OBJECT.

Let us now discuss the term IMMUTABLE. Considering that we understood what mutable stands for, it is obvious that the definition of immutable will have ‘NOT’ included in it. Here is the simplest definition of immutable– An object whose internal state can NOT be changed is IMMUTABLE.

Again, if you try and concentrate on different error messages, you have encountered, thrown by the respective IDE; you use you would be able to identify the immutable objects in Python. For instance, consider the below code & associated error message with it, while trying to change the value of a Tuple at index 0. 

#Creating a Tuple with variable name ‘foo’

foo = (1, 2)

#Changing the index[0] value from 1 to 3

foo[0] = 3
	
TypeError: 'tuple' object does not support item assignment 

Immutable Objects in Python

Once again, a simple code would be the best way to depict what immutable stands for. Hence, let us discuss the below code step-by-step:

#Creating a Tuple which contains English name of weekdays

weekdays = ‘Sunday’, ‘Monday’, ‘Tuesday’, ‘Wednesday’, ‘Thursday’, ‘Friday’, ‘Saturday’

# Printing the elements of tuple weekdays

print(weekdays)

Output [1]:  (‘Sunday’, ‘Monday’, ‘Tuesday’, ‘Wednesday’, ‘Thursday’, ‘Friday’, ‘Saturday’)

#Printing the location of the object created in the memory address in hexadecimal format

print(hex(id(weekdays)))

Output [2]: 0x1691cc35090

#tuples are immutable, so you cannot add new elements, hence, using merge of tuples with the # + operator to add a new imaginary day in the tuple ‘weekdays’

weekdays  +=  ‘Pythonday’,

#Printing the elements of tuple weekdays

print(weekdays)

Output [3]: (‘Sunday’, ‘Monday’, ‘Tuesday’, ‘Wednesday’, ‘Thursday’, ‘Friday’, ‘Saturday’, ‘Pythonday’)

#Printing the location of the object created in the memory address in hexadecimal format

print(hex(id(weekdays)))

Output [4]: 0x1691cc8ad68

This above example shows that we were able to use the same variable name that is referencing an object which is a type of tuple with seven elements in it. However, the ID or the memory location of the old & new tuple is not the same. We were not able to change the internal state of the object ‘weekdays’. The Python program manager created a new object in the memory address and the variable name ‘weekdays’ started referencing the new object with eight elements in it.  Hence, we can say that the object which is a type of tuple with reference variable name ‘weekdays’ is an IMMUTABLE OBJECT.

Also Read: Understanding the Exploratory Data Analysis (EDA) in Python

Where can you use mutable and immutable objects:

Mutable objects can be used where you want to allow for any updates. For example, you have a list of employee names in your organizations, and that needs to be updated every time a new member is hired. You can create a mutable list, and it can be updated easily.

Immutability offers a lot of useful applications to different sensitive tasks we do in a network centred environment where we allow for parallel processing. By creating immutable objects, you seal the values and ensure that no threads can invoke overwrite/update to your data. This is also useful in situations where you would like to write a piece of code that cannot be modified. For example, a debug code that attempts to find the value of an immutable object.

Watch outs:  Non transitive nature of Immutability:

OK! Now we do understand what mutable & immutable objects in Python are. Let’s go ahead and discuss the combination of these two and explore the possibilities. Let’s discuss, as to how will it behave if you have an immutable object which contains the mutable object(s)? Or vice versa? Let us again use a code to understand this behaviour–

#creating a tuple (immutable object) which contains 2 lists(mutable) as it’s elements

#The elements (lists) contains the name, age & gender 

person = (['Ayaan', 5, 'Male'], ['Aaradhya', 8, 'Female'])

#printing the tuple

print(person)

Output [1]: (['Ayaan', 5, 'Male'], ['Aaradhya', 8, 'Female'])

#printing the location of the object created in the memory address in hexadecimal format

print(hex(id(person)))

Output [2]: 0x1691ef47f88

#Changing the age for the 1st element. Selecting 1st element of tuple by using indexing [0] then 2nd element of the list by using indexing [1] and assigning a new value for age as 4

person[0][1] = 4

#printing the updated tuple

print(person)

Output [3]: (['Ayaan', 4, 'Male'], ['Aaradhya', 8, 'Female'])

#printing the location of the object created in the memory address in hexadecimal format

print(hex(id(person)))

Output [4]: 0x1691ef47f88

In the above code, you can see that the object ‘person’ is immutable since it is a type of tuple. However, it has two lists as it’s elements, and we can change the state of lists (lists being mutable). So, here we did not change the object reference inside the Tuple, but the referenced object was mutated.

Also Read: Real-Time Object Detection Using TensorFlow

Same way, let’s explore how it will behave if you have a mutable object which contains an immutable object? Let us again use a code to understand the behaviour–

#creating a list (mutable object) which contains tuples(immutable) as it’s elements

list1 = [(1, 2, 3), (4, 5, 6)]

#printing the list

print(list1)

Output [1]: [(1, 2, 3), (4, 5, 6)]

#printing the location of the object created in the memory address in hexadecimal format

print(hex(id(list1)))

Output [2]: 0x1691d5b13c8	

#changing object reference at index 0

list1[0] = (7, 8, 9)

#printing the list

Output [3]: [(7, 8, 9), (4, 5, 6)]

#printing the location of the object created in the memory address in hexadecimal format

print(hex(id(list1)))

Output [4]: 0x1691d5b13c8

As an individual, it completely depends upon you and your requirements as to what kind of data structure you would like to create with a combination of mutable & immutable objects. I hope that this information will help you while deciding the type of object you would like to select going forward.

Before I end our discussion on IMMUTABILITY, allow me to use the word ‘CAVITE’ when we discuss the String and Integers. There is an exception, and you may see some surprising results while checking the truthiness for immutability. For instance:
#creating an object of integer type with value 10 and reference variable name ‘x’ 

x = 10
 

#printing the value of ‘x’

print(x)

Output [1]: 10

#Printing the location of the object created in the memory address in hexadecimal format

print(hex(id(x)))

Output [2]: 0x538fb560

#creating an object of integer type with value 10 and reference variable name ‘y’

y = 10

#printing the value of ‘y’

print(y)

Output [3]: 10

#Printing the location of the object created in the memory address in hexadecimal format

print(hex(id(y)))

Output [4]: 0x538fb560

As per our discussion and understanding, so far, the memory address for x & y should have been different, since, 10 is an instance of Integer class which is immutable. However, as shown in the above code, it has the same memory address. This is not something that we expected. It seems that what we have understood and discussed, has an exception as well.

Quick check – Python Data Structures

Immutability of Tuple

Tuples are immutable and hence cannot have any changes in them once they are created in Python. This is because they support the same sequence operations as strings. We all know that strings are immutable. The index operator will select an element from a tuple just like in a string. Hence, they are immutable.

Exceptions in immutability

Like all, there are exceptions in the immutability in python too. Not all immutable objects are really mutable. This will lead to a lot of doubts in your mind. Let us just take an example to understand this.

Consider a tuple ‘tup’.

Now, if we consider tuple tup = (‘GreatLearning’,[4,3,1,2]) ;

We see that the tuple has elements of different data types. The first element here is a string which as we all know is immutable in nature. The second element is a list which we all know is mutable. Now, we all know that the tuple itself is an immutable data type. It cannot change its contents. But, the list inside it can change its contents. So, the value of the Immutable objects cannot be changed but its constituent objects can. change its value.

FAQs

1. Difference between mutable vs immutable in Python?

Mutable Object	Immutable Object
State of the object can be modified after it is created.	State of the object can’t be modified once it is created.
They are not thread safe.	They are thread safe
Mutable classes are not final.	It is important to make the class final before creating an immutable object.

2. What are the mutable and immutable data types in Python?

• Some mutable data types in Python are:

list, dictionary, set, user-defined classes.

• Some immutable data types are: 

int, float, decimal, bool, string, tuple, range.

3. Are lists mutable in Python?

Lists in Python are mutable data types as the elements of the list can be modified, individual elements can be replaced, and the order of elements can be changed even after the list has been created.
(Examples related to lists have been discussed earlier in this blog.)

4. Why are tuples called immutable types?

Tuple and list data structures are very similar, but one big difference between the data types is that lists are mutable, whereas tuples are immutable. The reason for the tuple’s immutability is that once the elements are added to the tuple and the tuple has been created; it remains unchanged.

A programmer would always prefer building a code that can be reused instead of making the whole data object again. Still, even though tuples are immutable, like lists, they can contain any Python object, including mutable objects.

5. Are sets mutable in Python?

A set is an iterable unordered collection of data type which can be used to perform mathematical operations (like union, intersection, difference etc.). Every element in a set is unique and immutable, i.e. no duplicate values should be there, and the values can’t be changed. However, we can add or remove items from the set as the set itself is mutable.

6. Are strings mutable in Python?

Strings are not mutable in Python. Strings are a immutable data types which means that its value cannot be updated.

Join Great Learning Academy’s free online courses and upgrade your skills today.

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Original article source at: https://www.mygreatlearning.com

#python 

Change AOL Password - How To Change AOL Password In Chrome Browser

If you can’t sign into an AOL email account, simply because you’ve forgotten the password? and Do you want to know How To Change AOL Password In Chrome Browser? you’re at the right place to seek out the instructions for reset aol password.

If you’ve cleared the cache in your Chrome Browser browser, but still experiencing issues, you’ll have to restore its original settings. this will remove adware, get obviate extensions you didn’t install, and improve overall performance. Restoring your browser’s default settings also will reset chrome browser security settings. A reset may delete other saved info like bookmarks, stored passwords, and your homepage. Confirm what info your chrome browser will eliminate before resetting and confirm to save lots of any info you do not want to lose.

In this article, I’m going to share all the methods for Change AOL Email Password. you ought to try one among them to Reset AOL Password In Chrome Browser by yourself.

How to Solve Forgot AOL Mail Password?

Steps for Change AOL Mail Password-
Before I will be able to share any instructions about the way to Change AOL Mail Password, I want to inform you, you ought to have access to a minimum of one recovery option. So you’ll plow ahead and reset your AOL password.

• Open an internet browser on your computer like- internet explorer, google chrome, or Mozilla Firefox.
• Go to aol.com
• Now click on check-in.
• Below the username and password box, you’ll see the forget password option. So click thereon.
• Now, this may ask you for your email address. So you would like to type your email address and click on the continue button.
• Here you would like to prove that you simply aren’t a robot. So simply accept the captcha code and click on continue again.
• After proving you’re not the robot, you’ll reach the subsequent screen. Here it’ll invite account verification.

For verifying the account ownership, you’ll plow ahead and choose anybody’s verification method, like- phone, security questions, etc. and verify the account ownership.

Be careful once you are verifying your account. One wrong step can also block your account.

1. Phone Verification – if you’ll choose phone verification for verifying the account ownership, you’ll get a code on your phone via call or SMS. that you simply need to enter into your computer.

2. Security questions- this is often the very easy method to verify the account ownership. All you would like to try to just answer the safety questions. Whatever you’ve got found out.

If you’ll verify the account ownership successfully, then you’ll reach the new password window. So you’ll create your password now. But whenever you’re creating the password, confirm you’re making a posh password.

After resetting the password, you’ll plow ahead and check out to login to your AOL account with a replacement password.

Furthermore, if you would like a moment solution for any AOL mail-related all query, you’ll contact our email customer care team. The professionals will assist you with the flowchart to vary your password or add a replacement account. you’re liberal to connect with us 24*7. Share your problem and obtain a reliable solution within a couple of seconds. Are you the one trying to attach AOL Customer Service? Contact us at +1-888-857-5157 and you can also visit our website.

Source: https://sites.google.com/view/recover-change-aol-key/blogs/how-to-change-aol-password-in-chrome-browser

#change aol password in chrome browser #change aol email password in chrome browser #change aol mail password in chrome browser