If you are a big data enthusiast and want to enter the field of big data, or if you are employing a development team to handle your big data requirements, you would find yourself pondering over this question many times. Is Python the best choice over the many other programming languages available? Which language should you train yourself or your staff in? Python or R or Hadoop? well, an article cannot solve your quandary, but read on if you need to find out what Python has to offer.
Python is an open source programing language, which is most popularly used in big data. Python Language is synonymous with flexibility, powerful yet easy to use features. Python has its USP in the rich set of utilities and the libraries it offers for analytics and data processing tasks. So, all in all, it is a given fact that among other options available Python maintains its popularity essentially because of it’s easy to use features, which supports big data processing.
Python was developed with the philosophy to bring coding to an open platform, where coding becomes easy, more readable, where one can write less number of lines and yet get the desired results. Keeping the objective in mind, a standard library was introduced, which contained ready to use tools for performing various tasks.
These features make Python the most preferred choice for software development, and mostly so for Artificial intelligence and Machine Learning.
To put it shortly you need to learn Python because……
- It offers a speedy learning curve and reduced development time, the syntax in Python is much cleaner and neater in comparison to other languages. It is easy to debug due to shorter codes. The modular architecture makes it easy to merely import and use a module rather than writing a large block of code. Great choice for beginners. Shorter and quicker codes reduce the development time drastically.
- You can automate the repetitive tasks, for lesser cognitively demanding tasks, tasks that need little decision making can be automatically programmed by writing a script in Python.
- It is the most common choice for data scientist and analytics because of the convenience of feature-rich modules in Python which makes it easy to conduct data analytics in an efficient manner.
- Python is an object-oriented language, so if you learn Python it will make it easy for you to switch to any other object-oriented language. You will only need to learn the syntax of the other language.
- It is the future for Artificial Intelligence and Machine Learning, which will be integrated in most functions in the very near future. Python becomes the premium choice for Machine learning algorithms mainly because of the portable extendable and scalable features of the language.
The field of data science and analytics, more specifically artificial intelligence and machine learning will only continue to flourish in the coming years. If you are looking to take a plunge in this field, then fluency in Python can be considered a prerequisite. Learning Python has minimal investment and maximum benefits, it then surely becomes an advantage to learn.
One should have a good grasp of technology, as its uses and advantages have seeped in almost all spheres of professional setups. If you are working in the field of IT, programmer to be specific, a quick way to upgrade your resume would be to learn Python. Python is considered to be the most commonly used programming languages. Hence for a programmer who is on the brink of embarking his career should learn Python.
So if you are considering learning to code, and be updated and efficient with your skills in the world of programming. Then further read on to understand five undisputable reasons you should learn Python.
Quick and Fast
Python is definitely an easy language to learn, to be true the language was designed keeping this feature in mind. For a beginner, the biggest advantage is that the codes are approximately 3-5 times shorter in Python than in any other programming language. Python is also very easy to read, almost like reading the English language, hence it becomes effective yet uncomplicated in its application.
The dual advantage is that a beginner will not only pick up faster but, will also be able to code complex programmes in a shorter amount of time. And an experienced programmer will increase productivity.
Big Corporates use Python
Python is one of the most favourite languages used at Google, and they are ever hiring experts. Yahoo, IBM, Nokia, Disney, NASA all rely on Python. They are always in search of Python web developers, and a point to note is that they are big pay masters. Hence learning Python equals to big Pay cheques.
Python for Machine Learning and Artificial Intelligence
The biggest USP of Python is that it is easy to use, flexible and fast, hence it is the preferred language choice. And especially so in computer science research. Through Python, one can perform complex calculation with a simple ‘import’ statement, followed by a function call, thanks to Python’s numerical computation engines. With time Python has become the most liked language for Machine Learning.
Python is Open Source and comes with an exciting Ecosystem
Python has been there for almost 20 years or so, running across platforms as an open source. With Python, you will get codes for, Linux, windows and MacOS. There is also a number of resources that get developed for Python that keeps getting updated. It also has a standard library with in-built functionality.
Nothing is Impossible with Python
And if the above reasons are not convincing, perhaps the best reason to learn Python, is that irrespective of what your career goals are you can do anything. Since it is easy and quick to learn, with it, you can adapt to any other language or more importantly environment. Be it web development, big data, mathematical computing, finance, trading, game development or even cyber security, you can use Python to get involved.
Python is not some kind of a niche language, and neither is it a small time scripting language, but major applications like YouTube or Dropbox are written in Python. The opportunities are great, so learn the language and get started.
Of late, a great topic of discussion is on the true meaning of Artificial Intelligence. As the field is witnessing progress there is a constant evolution in the meaning as well. In simple words, artificial intelligence is the ability of the computer to perform tasks commonly associated with intellectual human being. It is predicted to fundamentally reshape the way in which organisations work.
Artificial intelligence and Machine intelligence is often misunderstood as a substitute for each other. Machine learning is basically getting the computers to program for themselves, here it allows the data to internally train the data sets. Machine or Artificial intelligence on the other hand means ‘intelligent computers’, computers without human intervention capable of pattern discovery, discerning context, to reason, and to learn and improve themselves overtime.
What’s in the Future……?
In the future with this type of evolution, it will not necessarily be Humans v/s Computers, but man and computers working alongside in harmony to improve the way we work. So the employees who do routine manual or routine cognitive job roles, will have a high chance that their jobs will be replaced with computers and they will have the availability of time to invest in areas that they are interested or jobs that require advanced skills. Making machines responsible to do the repetitive tasks can go a long way. It will take the creativity and innovation quotient of the human race to enhanced levels. Furthermore, this technology is not only set to impact the workers with routine repetitive jobs, if your job is of routine cognitive nature then artificial or machine intelligence will play a role of a digital advisor, it will play a role where man and machine collaboratively work in tandem for betterment. Artificial learning and automation of certain jobs will then to a large extent become a good thing.
There are some researches which predicts that artificial intelligence will be responsible in making workers more productive and create new jobs. There is a belief that AI will help with automation that will not only assist companies to focus on higher skilled tasks and more creative jobs but will give them insights which will enable workplaces to use that knowledge in ways that cannot have been imagined so far.
Some stats on Artificial Intelligence:
- By 2020 85% of customer interactions will be handled without a human
- 44% of executives believe “artificial intelligence’s most important benefit is that automated communications that provide data that can be used to make decisions”
- By 2018 ‘customer digital assistance’ will recognise customers by face and voice across channels and partners.
- By 2020, smart agents will manage 40% of mobile interactions.
- 9% of business data technology have artificial intelligence solutions deployed.
The artificial intelligence market is estimated to reach $40 billion by 2020
In the future, you will witness an Artificial intelligence revolution in marketing, where smart data and machine intelligence in collaboration will use artificial intuition which ape’s human intuition. For e.g. creating advertisements whose images and phrases evolve based on viewer response.
However, reaching the state where organisations will be machine intelligent is not so easy. The majority of our efforts at present is on supervised learning, where we are training the computer on instances that are labelled with reinforcement, and doing that takes time. Also there is the impending challenge of embedding the technology into existing enterprise application. In doing that we will one day make the computer as intelligent as the human brain.
25 years ago the internet impacted the wider world, it revolutionised the way we existed, changed the way organisations functioned. We are at the identical brink of time where in the next 25 years Artificial Intelligence might have the same impact on the way we work and live.
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When it comes to predicting the value of AI, things can get a little vague and confusing. This is mainly because of the wide applications as well as the rapid evolvement of Artificial Intelligence. It is estimated by the Data Corporation, that the market for technologies of or related to Artificial Intelligence, is bound to increase up to $40 billion by the year 2020. While this market would deal with all those technologies that help in analysing unstructured data, it is believed that it will be generating productive improvements, which promise to be well over $60 billion worth of the United States market per year.
Consequently, a majority of investors have begun to discover and realize the true value of AI and as a result of this, more and more investments have begun to take place in the venture capitalist markets. Let’s talk about figures, the year 2013 saw about $757 million, being invested in AI start-ups, 2014 saw about $2.8 billion, 2015 saw around $2.3 billion and if these figures are anything but telling, it is guaranteed that the investments will only be growing in proportion for the coming years. The Mckinsey Global Institute has estimated that all the automating knowledge work, with Artificial Intelligence, is bound to generate anything around $5.2 trillion to close to $7 trillion. It is believed that the advancement in advanced robotics by primarily relying on Artificial Intelligence will generate anything up to $2 trillion. All of these estimates are made for up to the year 2025, which is barely a decade away.
Thus, we can conclude that the value of Artificial Intelligence is not only humongous, but it bound to increase manifold soon enough. It is believed by many experts that the AI has so much power, that it can go ahead to solve global issues like climate change and food insecurity. Artificial Intelligence already has and is bound to have a varied number of applications. Mapping poverty with satellite data, measuring literacy rates, cracking down on human trafficking rackets, preventing abusive internet tools from taking up actions are some of the social applications of AI that will definitely benefit the society in the near future.
When it comes to public safety, artificial intelligence could very well be applied for pinpointing the various happenings during crimes, for prediction of crime hotspots, for disposing of car bombs autonomously, for predicting the fire or earthquake risks of building accurately, for ensuring that every type of security screening is less invasive and so on. Industries would benefit majorly from AI as it would ensure the prevention of breakdowns or power cuts before they even take place, everything from intelligent manufacturing to automated factories could be very possible, improvement in terms of the dairy supply chains with the help of market forecasting would be a real thing and much more.
Thus AI shows a lot of promise in terms of changing the world for the better tomorrow and as a result of this, it would make a great career. There are many institutes in India like Imarticus Learning, which offer a number of comprehensive courses in Data Science, that would help an individual further their career in AI.
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The field of Artificial Intelligence seems to working on a winning streak. In the year 2005, the U. S Defence Advance Research Project Agency, held the DARPA Grand Challenge, which was supposedly held to spur development of autonomous vehicles, basically in order to make self-driven, smart cars. This challenge was taken up and successfully completed by 5 teams. In the year 2011, in a great competition of Jeopardy, the IBM Watson system, was successfully able to beat two long time, human champions of the same legendary game. Another great win of technology over the human race would be in the year 2016, when Google DeepMind’s AlphaGo system was able to successfully defeat the world champion of Go Player, who was reportedly the world champion for 18 consecutive times.
While these feats of technology over the human brain are extremely commendable, today the long surviving dream of humans, which basically revolved around developing technology to control their surroundings, has finally come to fruition. This has resulted in the form of Google’s Google Assistant, Microsoft’s Cortana, Apple’s Siri and Amazon’s Alexa. As a result of all of these AI (Artificial Intelligence) powered virtual assistants, people are able to make greater use of technology in order to live better lives.
Artificial Intelligence is considered to be a field of computer science, which is entirely devoted to the creation of computing machines and systems, all of which are able to perform operations that are similar to human learning and decision making. According to the Association for the Advancement of Artificial Intelligence, AI is, “the scientific understanding of the mechanisms underlying thought and intelligent behaviour and their embodiment in machines.” While these intelligence levels can never be compared to those of the humans, but they can certainly vary in terms of various technologies.
Artificial Intelligence includes a number of functions, which include learning, which primarily includes a number of approaches such as deep learning, transfer learning, human learning and especially decision making. All of these functionalities can later help in the execution of various fields such as cardiology, accounting, law, deductive reasoning, quantitative reasoning, and mainly interactions with people, in order to not only perform tasks, but also to learn from the environment.
While the recent changes may be extremely mind blowing, the promise of AI has always been existing since era of electromechanical computing, this began in the time period, after the World War 2. The first conference of Artificial Intelligence was held at the college of Dartmouth in the year 1956 and at that time, it was said that AI could be achieved within the time period of summer. Later on, in the 1960’s there were scientists, who claimed that in the next decade, it would be possible to see various machines controlling human lives. But it was in the year 1965, when the Nobel Laureate, Herbert Simon, who is supposed to have predicted the words, which would have some substance and which were, “In the next 20 years, it would be possible that machines would be able to do any work of labour that man can”.
With Artificial Intelligence, going in full fervour, the field which it has affected most in the field of Data Science. And as there are many who believe that there is a great to achieve in this field, have begun to get trained in the same by approaching professional training institute – Imarticus Learning.
We all know that Mark Zuckerberg of Facebook is strongly passionate about Machine Learning and Artificial Intelligence, but how has that impacted our everyday online social life?
You may think you’re just uploading a photo, but facebook knows how many people are there, whether you’re outside or inside, and if you’re smiling.
The technology that Facebook uses, Artificial Intelligence, is a rigorous science that focuses on designing systems that make use of algorithms that are much similar to that of our human brain. AI learns to recognize patterns from large amounts of data and come up with a comprehensive conclusion.
What does that have to do with how Facebook knows if I’m smiling or not?
Facebook is constantly teaching their machines to work better. By using deep learning, they train AI to structure through various processing layers and understanding an abstract representation of what the data could be. By using their system called “convolutional neural network”, the computer is able to go through layers of units and understand whether there is a dog in a photo.
Facebook works through layers. In the first layer, it is able to identify the edges of objects. In the second layer, it is able to detect combinations and identify it to be an eye in a face or a window in a plane. The next layer combines these further and identifies them to be either an entire face or a wing on a plane. The final layer is able to further detect these combinations and identifies if it is a person or a plane.
The network needs to be able to read the labels on the database and identify which of these are labeled as humans or plants. The system learns to associate the input with the label. The way facebook works is that it is able to now identify not only that there are humans in a photo, but how many humans, whether they are indoors or outdoors, and their actions, i.e. if they are sitting or standing.
However, a photograph that has been uploaded may need to be completely zoomed in for Facebook’s AI to understand intricacies if a person is smiling or not.
It may not always be perfect in its recognition, but it’s getting there.
A lot of information can be extracted from a photograph. Facebook is only going to get better with its AI and making use of big data.
Artificial Intelligence and Machine Learning is a concept that will be looked at in Imarticus’s Data Science Prodegree. This course is a cutting-edge program designed and delivered in collaboration with Genpact, a leader in Analytics solutions. Students get their hands-on learning with 6 industry projects and work with industry mentors.
Written by Tenaz Shanice Cardoz, Marketing & Communications.
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While a lot of experts believe that there’s some great stuff in store for the future of big data, it is also true that technology will be greatly advancing throughout 2017. This is why there are a number of complex facets of big data, which are increasing by the day. Various attributes of big data, such as artificial intelligence and cloud computing, are believed to have a huge impact on big data analytics. There are a number of factors that exhibit the potential to change or more likely determine the direction at which big data is moving. For instance, there will soon be a number of customers who would replace the businesses, in demanding various amounts of data, to look for the cheapest hotels and understanding climate issues and similar concepts. There is a very acceptable idea today, of a reality where it would be the customers, the common man, if you may, who would be demanding personalized, tailored artificial intelligence technology, to suit their particular needs and demands.
While these seem like mere examples, with a tinge of realism, there are absolute chances of these becoming a reality very soon.
Ten years ago, all the data that was ever generated and accumulated, made up the highest denominations of storage space, which was namely Gigabytes or Terra-bytes, but the recent few years have made an explosion of data, into what is known as exabytes; this term roughly refers to billions of Gigabytes of data. This is where we derive the term ‘big data’ from, it is to denote the humongous amounts of data that has been generated, all over the world, in such a short amount of time. Regardless of whatever happens in other aspects of this field, one thing we can be absolutely certain of. That is, that data will be continuously growing, which means that soon there will come a time, when we will be talking about Zettabytes, which roughly amounts for a trillion Gigabytes.
Artificial Intelligence began its advent, as just a buzzword which was continuously used by sci-fi movie enthusiast and was mainly used to refer to technology only seen in sci-fi movies and the likes. Today, this term is no longer reserved for those, who are obsessed with technological gizmos, or those involved in science. It has very well become a part of our everyday lives, through various examples, like Google’s Allo, Microsoft’s Cortana and Apple’s Siri. There are absolute indicators that AI has full potential of transforming, from something nice to have to very essential technology to have. There are so many changes and futuristic developments that big data can make today, as well as in the future.
One of the biggest prediction is the fact that big data can result in various advanced applications for fields of national security, customer behavior tracking, weather forecasting, HR, sports, health and so on.
One prediction is definitely going to happen, which is that big data will have a better, smarter and a huge impacting role to play in the future.
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2016 was almost a breakthrough year for the field of Big Data Science. From the concept of Artificial Intelligence being just an imaginative theory in movies, to its real use in understanding customers; from predictive analytics, being able to provide exactly what the customers are looking for, to employee enhancements technologies in HR, disease tracking interactive maps in the field of medicine to the various futuristic, interactive microwaves, T.Vs and refrigerators and so on. 2016 as a year has been a great one, barring a few minor debacles in terms of the functioning of big data.
As the new year has been ushered in, everyone’s in the I.T sector is waiting with bated breath of what new changes, will the new year of 2017, bring into the field of data science.
One thing that is a definite prediction in terms of big data, is the fact that it will soon be entering into the mainstream of IT and technology. This is owing hugely to the popularity of Hadoop and Spark among the various other data analytics tools. There is sure to be a rise in the number of firms and companies, which would entirely rely on the various functions of Hadoop and SAS, to help them in sorting the data.
We have only touched the tip of the iceberg, especially when it comes to all the data analytics tools in the market. For instance, SAS programming, was one software which was the default software used by a number of companies, across industries for everything apart from Data Analytics. While in the earlier scenarios, the use of cloud was to serve the purpose of storage, but today and the future trends point out to the fact, that there will be a number of companies which will start making the use of cloud for not only data storage, but also for data processing.
Now that the whole world is very well adjusted to the introduction of big data technologies, the rate at which it will be adopted, is definitely going to multiply.
There is a prediction that Big Data is bound to grow at a rate of 11.3 percent annually. There will be a great rise in the investments, which will basically be able to ensure the fast speed of data solutions, as people now don’t just want data, they are looking for fast data.
Predictive Analytics is bound to be the next big thing in terms of the various technologies, as these would be able to perfectly target the needs of the customers and provide perfect recommendations.
In terms of a career, Big Data Science is bound to increase in popularity and would be ever more so rewarding for almost all the data aspirants.