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Top Databases of 2017 to Watch Out For

Data processing is the most talked about topic of this year. From the figure below, you can comprehend that NoSQL and SQL databases are the ones most preferred by the respondents. 

 
Top Databases of 2017to Watch Out For
 

By putting together the percentage of respondents who found them fetching and who called them ‘extremely engaging’, we can conclude who the runner-up is. Here, NoSQL databases secure the second rank with 74.8%.

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Conducting Intensive Workshops – A Holistic, Exhaustive and Multidimensional Approach to Learning

Knowledge was scattered treasure; education organized it into art, commerce and science.

― Amit Kalantri – a magician, mentalist and an author

 

Conducting Intensive Workshops – A Holistic, Exhaustive and Multidimensional Approach to Learning

 

St. Stephen’s College, Delhi presents the magnanimous Academic Conclave 2017 – an initiative to endorse intellectual exuberance of the college and to strengthen interdisciplinary education across myriad fields of study. Often, the term ‘Academics’ is misinterpreted as ‘boring’ but once you attend this stellar event, you will definitely get a sneak peek of a perfect amalgamation of enthusiasm and comprehensive knowledge offered to the up-and-coming scholars of India. The intent is to establish a common accessible platform for incubation of ideas, interaction of thoughts and infestation of intellectuality and what can be better than host interactive workshop sessions! Besides lectures and keynote addresses, workshops are being conducted to encourage an easy interaction between the students and stalwarts of specific domains.

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How to Simulate Multiple Samples From a Linear Regression Model

In this blog post, we will learn how to simulate multiple samples efficiently. In order to keep the discussion, easy we have simulated a single sample with ‘n’ number of observations, and ‘p’ amount of variables. But in order to use the Monte Carlo method to approximate the distribution sampling of statistics, one needs to simulate many specimens with the same regression model.

 

How to Simulate Multiple Samples From a Linear Regression Model
How to Simulate Multiple Samples From a Linear Regression Model

 

The data steps in SAS in  most blogs have 4 steps mentioned for so. However, to simulate multiple samples, put DO loop around these steps that will generate, the error term and the response variable for very observation made in the model.

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Participate at the Atharva’17 “The Ultimate CMO Challenge, sponsored by DexLab Analytics

We have some intriguing news, The Ultimate CMO Challenge from the Delhi School of Economics, University of Delhi is being held and we are sponsoring the event. Participate at the Ultimate CMO Challenge if you a PG student or are pursuing a course in MBA.

 
Participate at the Atharva’17 “The Ultimate CMO Challenge, sponsored by DexLab Analytics
 

The first round will be an online round where participants would have to submit their solutions online. Problem case will be sent to the teams that have registered for the challenge, the solution to be submitted should be of 6 slides except the cover slides. One can mail their solutions to cmo.atharva@mibdu.org

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A robot too close to humans! Story of BINA 48

BINA 48 is the world’s most renowned and highly sought after humanoid robot in America. You can visit her there, by driving down a long winding dirt road just west of the Lincoln Gap in Bristol, Vt. Where sits two large yellow houses on a sprawling property that features ten solar panels and a dock over-looking the sunlit pond filled with trout, a homely porch decorated with rocking chairs.

Advances in Machine Learning and Data Analysis Bina 48

 

In the smaller of the two houses resides BINA 48, who is one of the most sought after humanoid who is based on a real personality – Bina Rothblatt.

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How to Assess Clustering Tendency: Unsupervised Machine Learning

How To Assess Clustering Tendency: Unsupervised Machine Learning

The meaning of clustering algorithms include partitioning methods (PAM, K-means, FANNY, CLARA etc) along with hierarchical clustering which are used to split the dataset into two groups or clusters of similar objects.

A natural question that comes, before applying any clustering method on the dataset is:

Does the dataset comprise of any inherent clusters?

A big problem associated to this, in case of unsupervised machine learning is that clustering methods often return clusters even though the data does not include any clusters. Put in other words, if one blindly applies a clustering analysis on a dataset, it will divide the data into several clusters because that is precisely what they are supposed to do. Continue reading “How to Assess Clustering Tendency: Unsupervised Machine Learning”

Here Are Four Predictions For AI This 2017!

Last year was the year, which saw artificial intelligence, went mainstream.

 

Here Are Four Predictions For AI This 2017!

 

By that, we do not mean just getting filtered raunchy photos on Twitter or getting the fake news suggestions on Facebook.

Here is what to look for in Artificial Intelligence for this New Year:

  • Driven by unprecedented financial support (along with a growing open source ecosystem), founders have been delivering artificial intelligence start-ups at a record high rate.
  • GE, Google, Intel, Microsoft, Facebook, Apple, Salesforce and Samsung, and several other name brands made rigorous AI investments last year.
  • There are now five million homes, which, are talking about their music and shopping choices with the help of Alexa from Amazon.
  • There is a whole new department of U.S. Department of Transportation Committee for self-driving cars. Even a few years ago, there were people talking about 2025 or so for the accessibility of self-driving cars (of level 5 autonomy), but this is a reality now, much before we could reach 2020. It is also amazing to think that self-driving cars may whittle down the 1.2 million annual deaths from automobiles.
  • Also in other interesting news, two AI unicorns just grew their horns, the Cylance in Silicon Valley and iCarbonX in China.
  • Also more than one-fifth of the MIT 50 smartest companies list, include AI as a core approach these days.

Continue reading “Here Are Four Predictions For AI This 2017!”

5 Major Problems in AI (Artificial Intelligence)

5 Major Problems in AI (Artificial Intelligence)

Before we get started with the topic, let us first get an idea about its background. Have you ever given a thought as to how many cats does it take to identify one cat?

In this article we will cover the five types of problems that people face with Artificial Intelligence (AI) i.e. we will address the all important question of – in which situation must one make use of AI (artificial intelligence)?

To have a better understanding of such concepts you can take up a Machine Learning course in Delhi.

Here is some background:

Just some time ago, we conducted a strategy workshop for a bunch of senior executives who are running a large multinational company. In that workshop, someone asked this question – “How many cats will it need to identify a cat?”

In this post, we will discuss the problems which can be uniquely resolved through Artificial Intelligence. While this may not be the exact taxonomy, but it still is pretty comprehensive. The main reason we have added extra emphasis on Enterprise AI issues, because we believe that this subject will have a deep impact on many mainstream applications, but despite that a lot of media attention focuses at the more esoteric avenues. Further, information about these concepts are available in our Machine Learning training course.

But before we delve into AI application types, we must discuss the main distinguishing characters between AI / Deep Learning / Machine Learning.

The term Artificial Intelligence by definition implies that machines can reason with the help of this feature. However, here is a better more complete list of AI characteristics:

  1. AI is capable of reasoning: they can solve complex problems through logical deductions on their own
  2. AI has knowledge: the capability to represent knowledge about the world or our understanding of it, that there are numerous events, entities, and varied situations that occur in the world and such elements have properties, which can be categorised.
  3. AI can plan: they have the ability to set and achieve targets. A specific state of the planet, which we desire along with a sequence of actions that can be undertaken which will help us, progress towards it.
  4. AI can communicate: they have the capability to comprehend well-written and spoken language.
  5. AI has its own perception: they have the ability to deduce things about their surrounding world through the visual images, sounds and other external sensory inputs just like us humans!

With developments in Deep Learning algorithms, AI is driven forward. The various deep learning algorithms can detect numerous patterns without having any prior definition of these features. And in a broader sense, Machine Learning means the application of any algorithm which can be applied against a set of data to discover a pattern within the same. Such algorithms have features like supervised, unsupervised, classification, segmentation, or regression. Moreover, while they are very popular, there are many reasons why Deep Learning algorithms may not make other Machine Learning algorithms.

Data Science Machine Learning Certification

The 5 major types of problems with AI:

Now that we have some background knowledge, we can now discuss the five major types of problems with AI:

Domain expertise: troubles involving reasoning based on a complex body of knowledge

This consists of tasks that are based on learning several knowledge bodies like financial, legal, and more, and then formulating a process where the machine will be able to simulate as an expert in the given field.

Domain extension: problems surrounding extension of a complex body of knowledge

In this case, the machine learns a complex body of knowledge like information regarding the existing medication and much more, and then suggests new ideas to the domain itself, like for instance new drugs for curing diseases.

Complex planning: projects that require complicated planning

There are many logistics and scheduling projects, which can be done by current (non AI) algorithms. But as optimization keeps developing and gets more complex AI would slowly grow.

Proficient communicator: tasks that involve developing existing communications

AI and deep learning can offer benefits to many communication modes such as intelligent agents, automatic and much more.

Fresh perception: projects that involve a unique perception

Deep learning and AI can be capable of producing newer forms of perception which enables new services like autonomous automotives and more.

Take up a Machine Learning Certification in order to make a change with AI.

 

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We Are Providing Corporate Trainings To Jones Lang Lasalle Pvt. Ltd.

We are happy to announce that we have recently begun our corporate training sessions for the multinational company Jones Lang LaSalle Pvt. Ltd. on Tableau Business Intelligence.

 
DexLab Analytics has started their Corporate Training sessions on Tableau BI for Jones Lang LaSalle Pvt. Ltd.
 

The company JLL are a professional service where they deal with investment management firm offering specialization in real estate services for clients seeking increase in value by owning, investing and occupying real estate. It is a Fortune 500 company and gathers annual revenue of USD 5.2 billion with gross revenue of USD 6.0 billion. They have more than 280 corporate offices and operate in 80 countries or more, their global work force is of 60,000. The firm provides management and real estate outsourcing services for realty portfolio for its clients. Their portfolios consists of 4.0 billion square feet which is 372 million square meters and have completed USD 138 billion in sales, financial transactions, and acquisitions on 2015.  Continue reading “We Are Providing Corporate Trainings To Jones Lang Lasalle Pvt. Ltd.”

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