0 comments on “Detailed Step-by-Step CIC Express Entry Instructions”

Detailed Step-by-Step CIC Express Entry Instructions

CIC-Express-Entry

Thank you all for the overwhelming response on the blog post Canada Immigration Express-Entry – The Golden-Mail

As a number of subscribers have requested a detailed post on a step-by-step instruction on how to apply for Express Entry process (in order), our team have compiled the same below:

How to apply for CIC Express Entry

1) Determine your eligibility by doing this CIC quiz:

http://www.cic.gc.ca/ctc-vac/ee-start.asp

2) Get your language test(s) done. You must get at least CLB 7 in each of the four sections for the Federal Skilled Worker (FSW), Provincial Nomination Program (PNP) or Canadian Experience Class (CEC) streams. But getting CLB 10 gives you maximum points for language.

How does CLB match back to the language tests? To know more, check the below: http://www.cic.gc.ca/english/resources/tools/language/charts.asp

3) Get your qualifications assessed by doing an Education Credential Assessment. Details here –> http://www.cic.gc.ca/english/immigrate/skilled/assessment.asp

4) Determine the code that best applies to you on the National Occupation Classification (NOC) list http://www.cic.gc.ca/english/immigrate/skilled/noc.asp

The occupation must be NOC 0, A, or B for FSW or CEC.

5) When you have those in hand you create your express entry profile. http://www.cic.gc.ca/english/immigrate/skilled/profile.asp

and

Register for the Job Bank

http://www.jobbank.gc.ca/home-eng.do?lang=eng

You’ll be given points based on your age, education, number of years work experience, and language skills. The points system is detailed here –>

http://www.cic.gc.ca/english/express-entry/grid-crs.asp

You’ll be in a pool with thousands of other applicants

http://www.cic.gc.ca/english/immigrate/skilled/pool.asp

Of course, the more points you have the better. The max is 1200, with 600 of those points coming from your ability to snag a PNP or a job offer with a very hard to get Labour Market Impact Assessment http://www.cic.gc.ca/english/work/employers/lmo-basics.asp

For CEC applicants, the max is 600 but someone who has no work experience in Canada who is only eligible for FSW can only get up to 520 points.

6) Finally, wait for your invitation to apply (ITA). But in the interim you will need to do the following:

a) Have your application fee (C$550 each for principal applicant and spouse) and right of permanent resident fee (C$490 each for principal applicant and spouse) ready
http://www.cic.gc.ca/english/information/fees/fees.asp

b) Identify how you will provide proof of funds 

http://www.cic.gc.ca/english/immigrate/skilled/funds.asp

c) Check out what is required for the Police Clearance  Certificates 

http://www.cic.gc.ca/English/information/security/police-cert/index.asp

d) Find out how long it takes to get a date for the Medical Exam. http://www.cic.gc.ca/english/information/medical/medexams-perm.asp

e) Contact previous and current employers about them providing Job letters. You must have at least 12 months of full-time, or an equal amount in part-time, skilled work experience. Full-time work means at least 30 hours of paid work per week. Work experience while you were a full-time student does not count.

f) Research Cities in the province(s) where you want to live.

RELATED POSTS: The Journey Begins… Landing in Canada as an Immigrant

0 comments on “History of India”

History of India

History_of_India

HISTORY OF INDIA

It’s amazing to learn about the Indian History which we often miss out in schools. I never knew there was a Greek Indian Kingdom in India for a significant time till I checked out the map of Empires of India. I find it quite surprising that the British were the first to have the entire Indian Subcontinent under their control, with the Mughal Empire coming second with only the south and some parts of the east outside their control.

 

Romilla Thapar’s book Early India from the origins to 1300 AD is a great book to start learning about this era.

FACTS ABOUT EMPIRES OF INDIA

​It is believed that there was a Greek ambassador known as Megasthenes in the Mauryan Empire. Mouryas and Guptas ruled from Arabian Sea to Bay of Bengal, covering both the populous Indus and Ganges valleys, that was an achievement then. British could rule mostly because of technological advancements in shipbuilding.

The level of control enjoyed in the Deccan by the Mughals probably exceeded that of the Delhi Sultanate, and the Guptas and the Mauryas (in that order). None of them were able to truly consolidate their holdings in the Deccan, with their large territorial dominance lasting ~50 years at the most. Why? Technology, as simple as that.

By the age of the Mughals, shipbuilding, gunpowder etc. made it easier to build nations. The notion of currency, banking institutions, tax codes etc. were much better developed. Armies were professional, weaponry was far more advanced. Tribal kings would wilt under Mughal artillery barrage but could probably give a tougher fight to a Mauryan army.

0 comments on “Samsung’s Upcoming Foldable Phone”

Samsung’s Upcoming Foldable Phone

samsung_foldable_phone

Samsung’s Upcoming Foldable Phone

It’s finally official for all Samsung lovers.

via GIPHY

Yes, Samsung has finally revealed its groundbreaking foldable phone after years of speculation, rumors, teases and mocked up protoypes.

Despite the media hype and teases from Samsung, this event never really hinged on the foldable phone. The developer’s conference is intended, naturally, for developers, and covered a whole load of inside-baseball updates that general consumers wouldn’t be interested in. And then, in the middle of it, came the much fabled Samsung folding phone. Or rather, the screen technology that will be key to the folding phone.

The key to Samsung’s folding phone is in its Infinity Flex display. The company aren’t referring to this device as a ‘new phone’, but more as a new range of devices. The focus for the brand isn’t on a one-off phone with an innovative new angle, but more the way the new technology could be applied to a range of products.

The biggest challenge in the design was making the screen thin enough to fold, and Samsung boasted that it had managed to reduce the thickness of its polarizing display component by 45%. This is essential, as it’s this component that handles the way the screen dissipates light, so your view isn’t obscured by reflections.

While the hands-on time with the display was brief, a presentation that followed told us more about the abilities of the Infinity Flex, claiming that it was not only foldable, but also rollable and stretchable.

When Will the Folding Phone be Released?

We knew that the folding phone was close – Samsung CEO DJ Koh had been dropping more and more elaborate hints in the past few months. However, if you’re expecting one under the Christmas tree this year, you’re going to be disappointed.

The technology will apparently be going into mass production within the next few months, according to Samsung, so it’ll be 2019 before you can walk into a store and buy one. The precise date remains to be seen, and the fact that we haven’t even seen the final version of the product yet means it won’t be for some time.

Then there’s the price. No word was given on the cost of the phone, but you should probably start saving now. Samsung is manufacturing an innovative display, and that doesn’t come cheap. Luckily, early adopters have deep pockets, but for the average consumer, the price tag will likely be an eye-popper.

Will it use this new technology to regain it’s edge over Apple? Only time can tell !

We know that phones are getting bigger and bigger in size which is making it almost practically difficult to handle. But we all want a bigger screen.

Advantages:

  • Multitasking – You’ll be able to operate 3 phone screens separately or 1+1 tablet and phone screen simultaneously. This is a huge boon for all the multitaskers.
  • Bigger and beautiful screen – You’ll be able to carry a tablet but it will actually be a size of a phone. The video and gaming experience will be beyond the expectations.

Disadvantages:

  • Too thick – The picture tells us that this phone will be very thick and kind of ugly when folded. This will make it heavier in the age of slim phones.
  • Terrible battery – Running 3 phone screens on a phone is not a joke. The battery will be poor, it is very logical. Forget about surviving for a whole day while playing high-end games.

Is it worth buying?

For normal users, maybe not. It will be expensive and a new technology takes time to develop. This smartphone will be facing initial undesired problems.

It might not go flop provided that it will not have major bugs during the release.

However, it might not get an instant hit as well.

0 comments on “Google’s Future Competitor”

Google’s Future Competitor

Google's_Future_Competitor

Who’s Google’s Future Competitor?

We all know “Google” for the past 20 years as the biggest company which provides services like Gmail, Search Engine, Mobile OS, YouTube etc.

Ever wondered how they make profit? As we all know, they earn money only from their advertisement tool called Google AdWords. Facebook uses similar tools to earn money which is called Facebook Adverts (Advertising Tool).

Now as we know that both Google & Facebook earn money using the same methodology, we might think them to be a competitor of each other. Isn’t it? But the reality is something different ! Let’s find out the inside story.

Data Sharing Pipeline

If you slightly change your vision, you will realize that it’s a partnership business. I know this because Facebook & Google share their user information with each other. Yes ! your searches are all recorded and you certainly don’t have any privacy. Do you know how advertisers track you online to show only relevant Ads based on your interests?

Thanks to big companies like Google and Facebook !!!

For Example, if you search “Pizza Order Online” in any of the Google platforms like Play Store, Chrome or Search Engine, your information is recorded and that data could be shared to Facebook network immediately.

And the next minute, you see Kites Cafe’s Facebook Ad.

So, both have shared their customers data and their revenue share depends upon the partnership & performances of online users. The user has been tracked by the re-marketing technique which uses it to show the ad based on your interest. So, this AD can follow you wherever you go and whatever platform you use. Moreover, Google gets data from it’s own partners like YouTube, Google Play-store, Android OS and Google Search Engine.

Who’s Google’s real Competitor?

When it comes to competition for search engine traffic, Google isn’t most worried about Microsoft Bing or Yahoo as a threat — actually, it’s Amazon.com. That’s what Google executive Eric Schmidt thinks.

But while the two companies compete on a number of levels — from phones to cloud services to drones to search engines — there is also some “co-operation” between the two. For example, Amazon was the biggest spender on Google search ads in the U.S. last year, spending a whopping $157.7 million.

E commerce Evolution

Yes! every big company wants to enter the e-commerce platform. Google & Facebook are in the process of starting their e-commerce platform soon. According to market research, only the Online Retail Market will have the potential to rule the world business in the upcoming years which is exactly what Amazon is doing.

Voice Assistant

Amazon introduced it’s new voice assistant device called Amazon Echo which can be used in home automation functions. To compete in this space, even google introduced it’s voice assistant technology product called Google Home which can used for the same purpose.

Artificial Intelligence’s Entry

Sometimes I have thought about Google to become a sky-net which I have seen in the Terminator movie. In my early days, one of my colleague warned me not to underestimate Google and it’s products. Then I started being aware of their business & and their products. All the changes & updates reminded me of the sky-net. All data under one data center. Terminator movie clearly explained that the world’s last day will come because of the robotics war.

Example, if we take top companies in the world, they are ready to use advanced technology. Amazon & Domino’s have a plan to increase their door step delivery by drones.

These drones can scan the customers house for up-sales. But this not related to our topic, so let’s go to conclude the topic.

Anything under human control is better for human living, otherwise if we go for machine learning to survive the competition, we may have to face the last day of the world soon.

Anyhow we need to have an awareness of the advancement in technology which can rule the world in the next 20 years.

0 comments on “Python 3.x”

Python 3.x

1. How to use value if not null else use value from next column in pandas?

2. How to rename columns in pandas?

3. How to sort a dictionary by value?

 

1. How to use value if NOT NULL else use value from Next Column

How to Use Value

if

Not Null,

Else

Use Value From Next Column

Given the following dataframe:

import pandas as pd
df = pd.DataFrame({'COL1': ['A', np.nan,'A'], 
                   'COL2' : [np.nan,'A','A']})
df
    COL1    COL2
0    A      NaN
1    NaN    A
2    A      A

How to create a column (‘COL3’) that uses the value from COL1 per row unless that value is null (or NaN). If the value is null (or NaN), how to use the value from COL2.

The desired result is:

   COL1    COL2   COL3
0    A      NaN    A
1    NaN    A      A
2    A      A      A

SOLUTION:

In [8]: df
Out[8]:
  COL1 COL2
0    A  NaN
1  NaN    B
2    A    B

In [9]: df["COL3"] = df["COL1"].fillna(df["COL2"])

In [10]: df
Out[10]:
  COL1 COL2 COL3
0    A  NaN    A
1  NaN    B    B
2    A    B    A

2. How to rename columns in pandas

I have a DataFrame using pandas and column labels that I need to edit to replace the original column labels.

I’d like to change the column names in a DataFrame A where the original column names are:

['$a', '$b', '$c', '$d', '$e'] 

to

['a', 'b', 'c', 'd', 'e'].

I have the edited column names stored it in a list, but I don’t know how to replace the column names.

SOLUTION:

Just assign it to the .columns attribute:

>>> df = pd.DataFrame({'$a':[1,2], '$b': [10,20]})
>>> df.columns = ['a', 'b']
>>> df
   a   b
0  1  10
1  2  20

 

3. How to sort a dictionary by value

I have a dictionary of values read from two fields in a database: a string field and a numeric field. The string field is unique, so that is the key of the dictionary.

I can sort on the keys, but how can I sort based on the values?

SOLUTION

It is not possible to sort a dictionary, only to get a representation of a dictionary that is sorted. Dictionaries are inherently orderless, but other types, such as lists and tuples, are not. So you need an ordered data type to represent sorted values, which will be a list—probably a list of tuples.

For instance,

import operator
x = {1: 2, 3: 4, 4: 3, 2: 1, 0: 0}
sorted_x = sorted(x.items(), key=operator.itemgetter(1))

sorted_x will be a list of tuples sorted by the second element in each tuple. dict(sorted_x) == x.

And for those wishing to sort on keys instead of values:

import operator
x = {1: 2, 3: 4, 4: 3, 2: 1, 0: 0}
sorted_x = sorted(x.items(), key=operator.itemgetter(0))

In Python3 since unpacking is not allowed we can use

x = {1: 2, 3: 4, 4: 3, 2: 1, 0: 0}
sorted_by_value = sorted(x.items(), key=lambda kv: kv[1])
0 comments on “Top 30 U.S. Companies by Revenue”

Top 30 U.S. Companies by Revenue

Top_US_Companies_by_Revenue

The Top 30  U.S. companies are listed below based on their total revenue in the financial year ending on or before Jan 31, 2018

Assumptions: Some of these companies are involved in multiple economic sectors; the Infograph shows only their primary ones.

Top 30  U.S. companies by Revenue

Top_30_US_Companies_by_Revenue

You may be wondering, “How is Google not here?!” The answer is Google is a subsidiary of Alphabet Inc., and Alphabet is shown here.

Home Depot receives more money that Microsoft in sales, however their margins are much lower so their expenses are higher and earnings are much lower than Microsoft.

Interesting to note that San Francisco has 5 and Seattle has 3. L.A. has 0.

6 of the top 30, and 4 of the top 15 are Healthcare Companies.

The “Change” percentage refers to how much the company’s revenue has grown or shrunk since it’s previous fiscal year.

 

Top_30_US_Companies_by_Revenue_Change

0 comments on “How to be Happy in Life”

How to be Happy in Life

How_to_be_Happy

4 Hormones to be Happy in Life

Ever wondered How to be HAPPY in Life? Friends, as I sat in the park after my morning walk, My wife came and slumped next to me. She had completed her 30-minute jog. We chatted for a while. She said she is not happy in life. I looked up at her sheer disbelief since she seemed to have the best of everything in life.
“Why do you think so?” “I don’t know. Everyone tells I have everything needed, but I am not happy. “Then I questioned myself, am I happy?  “No,” was my inner voice reply. Now, that was an eye-opener for me. I began my quest to understand the real cause of my unhappiness, I couldn’t find one.

I dug deeper, read articles, spoke to life coaches but nothing made sense. Even started Artwork to find HAPPYNESS and Wellbeing. At last my doctor friend gave me the answer which put all my questions and doubts to rest. I implemented those and will say I am a lot happier person.

She said there are four hormones which determine a human’s happiness –

1. Endorphins,
2. Dopamine,
3. Serotonin, and
4. Oxytocin.
It is important we understand these hormones, as we need all four of them to stay happy.

Endorphins

Let’s look at the first hormone the Endorphins. When we exercise, the body releases Endorphins. This hormone helps the body cope with the pain of exercising. We then enjoy exercising because these Endorphins will make us happy. Laughter is another good way of generating Endorphins. We need to spend 30 minutes exercising every day, read or watch funny stuff to get our day’s dose of Endorphins.

Dopamine

The second hormone is Dopamine. In our journey of life, we accomplish many little and big tasks, it releases various levels of Dopamine. When we get appreciated for our work at the office or at home, we feel accomplished and good, that is because it releases Dopamine. This also explains why most housewives are unhappy since they rarely get acknowledged or appreciated for their work. Once, we join work, we buy a car, a house, the latest gadgets, a new house so forth. In each instance, it releases Dopamine and we become happy. Now, do we realize why we become happy when we shop?

Serotonin

The third hormone Serotonin is released when we act in a way that benefits others. When we transcend ourselves and give back to others or to nature or to the society, it releases Serotonin. Even, providing useful information on the internet like writing information blogs, answering peoples questions on Quora or Facebook groups will generate Serotonin. That is because we will use our precious time to help other people via our answers or articles.

Oxytocin

The final hormone is Oxytocin, is released when we become close to other human beings. When we hug our friends or family Oxytocin is released. The “Jadoo Ki Jhappi” from Munnabhai does really work. Similarly, when we shake hands or put our arms around someone’s shoulders, various amounts of Oxytocin is released.

So, it is simple, we have to exercise every day to get Endorphins,
We have to accomplish little goals and get Dopamine,
We need to be nice to others to get  Serotonin and
Finally hug our kids, friends, and families to get Oxytocin and we will be happy. When we are happy, we can deal with our challenges and problems better.

Now, we can understand why we need to hug a child who has a bad mood.

So to make your child more and more happy day by day …

1.Motivate him to play on the ground – Endorphins 

2. Appreciate your child for his small big achievements – Dopamine 

3. Inculcate sharing habit through you to your child – Serotonin 

4. Hug your child – Oxytocin

Please share the valuable and essential for the current generation.

0 comments on “How to Increase your Adsense CPC Pay – Simple Tweaks”

How to Increase your Adsense CPC Pay – Simple Tweaks

If you are trying to make money online, you must have realized that it can be quite hard, especially if you are monetizing your blog solely via ads.

A successful Adsense publisher needs not only a lot of traffic but also needs that traffic to engage with the ads that are being displayed on the website.

In the blogging world, you can either write articles that will compete for clicks that will pay a few cents or be strategic and write content that will pay the big bucks. Adsense CPC that you get paid will be contingent on the topic that you choose to write about.

If you are serious about making money online with Adsense, I suggest you target these top paying keywords and industries.

Below are the Top 10 Highest Paid Adsense Keywords for 2018

  1. Insurance $57 CPC
  2. Gas/Electricity $54 CPC
  3. Mortgage $47 CPC
  4. Attorney $47 CPC
  5. Loans $44 CPC
  6. Lawyer $42 CPC
  7. Donate $42 CPC
  8. Conference Call $42 CPC
  9. Degree $40 CPC
  10. Credit $38 CPC

Let’s take an example and understand how to make thousands of dollars each month by profiting from this data.

As you can see, top most CPC is for Insurance. So let’s say you write a perfectly SEO’ed article in which you are discussing insurance companies and are able to get your blog post high on google rankings, then you should be getting a good amount of high quality traffic to your site that will hopefully translate into more Adsense revenue.

Let’s take another example of a top paying keyword such as mesothelioma which pays $169+ per click. If you can utilize this data and provide references to the best lawyers, you can get paid as much as $169 for a single click on this ad.

Adsense_Highest_CPC

Top Paying Insurance Related Adsense Keywords

The insurance companies surely make a killing from those outrageous premiums they charge us. Otherwise how could they afford all those TV commercials and these crazy spend on Adwords? If you are in the insurance blogging space, kudos to you. You’ve picked a winner.

Keyword Volume KD CPC (USD) Competition Results
compare car insurance 70 78.04 469.12 1 5,720,000
auto insurance troy mi 10 66.48 420.29 0.84 1,080,000
car insurance comparison quote 10 77.7 342.54 0.88 2,400,000
cars with cheapest insurance rates 40 85 316.47 0.89 3,200,000
best learner driver insurance 10 67.65 300.26 0.77 830,000
insurance quotes young drivers 10 76.73 299.63 0.94 6,490,000
automobile club inter-insurance 20 84.42 299.49 0.81 783,000
car insurance personal injury 10 82 298.54 0.95 2,210,000
auto insurance conroe tx 40 69 298.08 0.82 443,000
auto insurance philadelphia pa 170 63.03 293.14 0.48 1,330,000

And lastly, how could I forget this…

Target these countries if you want to earn 10x more

Aiming for the right countries can really skyrocket your Adsense earnings. Here are the top 10 countries to target:

No. Country Avg. CPC ($) Max. CPC ($) Avg. CTR % Average RPM ($)
1 United States (US) 0.40 – 2.3 >50 2-3 2.04
2 Canada 0.50 – 2 >30 2 1.83
3 United Kingdom (UK) 0.10 – 1.6 >19 1-2 1.37
4 Germany 0.40 – 1 >11 1-3 2.62
5 Thailand 0.30 – 1 6 2 1.6
6 United Arab Emirates (UAE) 0.15 – 3.1 11 4 2.07
7 Japan 0.20 – 0.85 4 3 2.44
8 Switzerland 0.20 – 1 6 3 2.35
9 Italy 0.10 – 0.50 3 1-3 0.73
10 China 0.10-0.30 4 1-2 0.9

So now do you know how to make $50 a day with Adsense?

In my blog, I have used Bitcoin keywords which helps me earn a good revenue from Ads.

I don’t know about you, but 50 bucks a day on Ads sounds like a good passive income to me ($1.5k/mo).

Let’s run some calculations to see what it would take to make $50/day on Adsense.

First, some assumptions.

  • You are targeting US readers (as we saw earlier, US ads pay the most on average)
  • Your CTR (click-through rate) is 1% (i.e. 1% of visitors click on ads)
  • Your CPC is $0.50 (your niche is strong but your site is just getting started)
  • Your RPM (revenue per 1000 impressions) is $2

With these numbers we can now calculate how many visitors we need to earn our target amount.

The formula is = Visitors * CTR * CPC + Visitors/1000 * RPM 

So with 7,500 visitors per day we obtain around $50/day on Adsense.

(7,500 * 1% * $0.5 + 7,500/1000*$2 = $52.5/day)

But how do you obtain 7,500 page views per day? Is that reasonable?

Yes, it is reasonable. To do that, you can either

  • Produce 7-8 articles that get 1000 page views (hard) – My blog on How to become a millionaire does get 1000 page views.
  • Produce 75 articles that get 100 page views (much easier)

Conclusion

You can always run an Experiment (found under Optimization > Experiments) and see if blocking your ads yields more revenue or not.

You can also test if showing 50% of your total ads vs. 100% of ads yields more revenue.

Google Adsense experiments typically last for 30-40 days, up to 100 days (depending on your experiment and traffic).

0 comments on “How to protect yourself from Ransomware (Cryptolocker)”

How to protect yourself from Ransomware (Cryptolocker)

Ransomware_Malware_CryptoLocker

Wondering how to prevent yourself from Ransomware or Malware? Then, let’s first try to understand the meaning of Ransomware as well as CryptoLocker.

What is Ransomware?

Ransomware is a malware that locks your computer and mobile devices or encrypts your electronic files. When this happens, you can’t get to the data unless you pay a ransom. However this is not guaranteed and you should never pay!

What is CryptoLocker?

CryptoLocker is a family of ransomware whose business model (you must be surprised, but a malware is also a business to some!) is based on extorting money from users. This continues the trend started by another infamous piece of malware which also extorts its victims, the so-called ‘Police Virus’, which asks users to pay a ‘fine’ to unlock their computers. However, unlike the Police Virus, CryptoLocker hijacks users’ documents and asks them to pay a ransom (with a time limit to send the payment).

Malware installation

CryptoLocker uses social engineering techniques to trick the user into running it. More specifically, the victim receives an email with a password-protected ZIP file purporting to be from a logistics company.

Important Key Points to note about Ransomeware:

  • Most of the times, you are not able to get your data back even after paying a ransom.

  • Sometimes, your data isn’t even encrypted – it’s just hidden. In this case, you can get your data back without paying a ransom.

  • Keeping a regular, separate backup of your files takes all the power away from ransomware.

  • Unless your data is extremely valuable, do NOT pay a ransom.

Ransomware_CryptoLocker

How to prevent Ransomware:

Good News: Prevention is possible. Following simple cyber security advice can help you to avoid becoming a victim of ransomware.

Bad News: Unfortunately, in many cases, once the ransomware has been released into your device there is little you can do unless you have a backup or security software in place.

0 comments on “Machine Learning 101 to Boost your Predictive Analytics”

Machine Learning 101 to Boost your Predictive Analytics

Predictive_Analysis_Machine_Learning

How to effectively use Machine Learning to boost your predictive analytics? 

First let’s try to understand the differences between Machine Learning and Predictive Analytics

Machine Learning Predictive Analytics
It is an overall term encompassing various subfields including predictive analytics. It can be treated as a subfield of machine learning.
Heavily coding oriented. Mostly standard software oriented where a user need not code much themselves
It is considered to be generated from computer science i.e. computer science can be treated as the parent here. Statistics can be treated as a parent here.
It is the technology of tomorrow. It is so yesterday.
It is machine dominated by many techniques that are hard to understand but work like charm like deep learning. It is user dominated with techniques that must be intuitive for a user to understand and implement.
Tools like R, Python, SaaS are used. Excel, SPSS, Minitab are used.
It is very broad and continuously expanding. It has a very limited scope and application.

75% of Business leaders state ‘growth’ as the key source of value from analytics but only 60% of those leaders have predictive analytics capabilities. So what’s preventing the businesses from achieving predictive analytics capabilities? The major roadblock is applying the right set of tools, which can pull powerful insights from this stockpile of data. But first, a big data system requires identifying and storing of digital information (lots of!!). Using Machine learning and Artificial Intelligence algorithms, businesses can optimize and uncover new statistical patterns which form the backbone of predictive analytics.

Forms of Data Analysis

Organization with huge data can begin analytics. Before beginning data scientists should make sure that predictive analytics fulfills their business goals and is appropriate for the big data environment.

Let’s take a quick look at the three types of analytics –

Descriptive analytics – It is the basic form of analytics which aggregates big data and provides useful insights into the past.

Predictive analytics – Next step in data reduction; It uses various statistical modelling and machine learning techniques to analyze past data and predict the future outcomes

Prescriptive analytics – New form of analytics which uses a combination of business rules, machine learning and computational modelling to recommend the best course of action for any pre-specified outcome.

Neural networks – Building blocks of Data Analysis

Neural network is a system of hardware and software mimicked after the central nervous system of humans, to estimate functions that depend on huge amount of unknown inputs. Neural networks are specified by three things – architecture, activity rule and learning rule.

According to Kaz Sato, Staff Developer Advocate at Google Cloud Platform “A neural network is a function that learns the expected output for a given input from training datasets”. A neural network is an interconnected group of nodes. Each processing node has its own small sphere of knowledge, including what it has seen and any rules it was originally programmed with or developed for itself.

Neural Network for predictive analytics

In short neural networks are adaptive and modify themselves as they learn from subsequent inputs. For example, below is a representation of a neural network that performs image recognition for ‘humans’. The network has been trained with a lot of sample human and non-human images. The resulting network works as a function that takes an image as input and outputs label human or non-human.

Neural network - Image recognition

Building predictive capabilities using Machine Learning and Artificial Intelligence

Let’s implement what we have learned about neural networks in an everyday predictive example. For example, we want to model a neural network for banking system that predicts debtor risk. For such a problem we have to build a recurrent neural network which can model patterns over time. RNN will require huge memory and a large quantity of input data. The neural system will take data sets of previous debtors. Input variables can be age, income, current debt etc  and provide the risk factor for the debtor. Each time we ask our neural network for an answer, we also save a set of our intermediate calculations and use them the next time as part of our input. That way, our model will adjust its predictions based on the input that it has seen recently.

Neural network - Debtor risk analysis

Uses cases for Machine Learning based predictive analytics

As Machine Learning and Artificial Intelligence landscape evolves predictive analytics is finding its way into more business use cases. Coupled with Business intelligence (BI) tools such as Domo and Tableau, business executives can make sense of big data.

Some prospective use cases for ML-based predictive analytics are:

E-commerce –  Using ML businesses can predict customer churn and fraudulent transaction. Also predicting which product customer will click on.

Marketing – There are many examples of ML in B2B marketing. Common use case is identifying and acquiring prospects with attributes similar to existing customers. They can also prioritize known prospects, leads, and accounts based on their likelihood to take action.

Customer service – Satisfaction Prediction made by Zendesk uses a machine learning algorithm to process results of historical satisfaction surveys, learning from signals such as the total time to resolve a ticket, response delay, and the specific wording of tickets cross-referenced with customer satisfaction ratings.

Medical Diagnosis – Medical professionals can use a program modelled using ML to predict the likeliness of a particular illness. The model will use a database of patient records and will make predictions based on symptoms exhibited by the patient.

Organizations and technology companies are employing machine learning based predictive analytics to gain an edge over the rest of the market. Machine learning advancements such as neural networks and deep learning algorithms can discover hidden patterns in unstructured data sets and uncover new information. But building a comprehensive data analysis and predictive analytics strategy requires big data and progressive IT systems.