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Tag: Python Certification

Supervised Learning: It’s Not As Difficult As You Think

Posted on by Imarticus Learning
Reading Time: 2 minutes

Supervised learning is a concept that has been around for decades, but it’s still not as widely understood as other machine learning techniques. This post will help you know what supervised learning is and how you can apply it to your own projects.

What Is Supervised Learning?

Supervised learning allows you to predict the value of a target variable based on an input variable. The input variable, called the feature variable, indicates or classifies future data points concerning their labels. The label refers to whether or not something falls under one category or another; in this case, we’re predicting whether or not our training set will match up with future samples.

Machine learning differs from classical programming because it uses algorithms instead of instructions for how the program should work. We get more flexible, powerful, and capable programs than ever!

Benefits of Supervised  learning

The training data will give you a clear sense of the classes. You can easily comprehend the process of supervised learning. Unsupervised learning makes it difficult to understand the inner workings of the computer, how it learns, etc.

Before providing the data for training, you can determine the precise number of classes. You may train the classifier in a way that has a perfect decision boundary to precisely discriminate between distinct classes, allowing you to be very exact about the description of the classes. You don’t necessarily need to retain the training data in your memory once the entire program is through. Instead, you can stick with your choice.

What Are Some Practical Use Cases For Supervised Learning?

You can use Supervised learning in many real-world applications. Image recognition, natural language processing, and financial forecasting are just a few examples of supervised learning being used to solve problems we all encounter daily. Supervised learning is a powerful tool that you can use in many different fields. It has been around for a long time, but not many people know because it’s not as flashy as machine learning or deep learning. 

Supervised learning is also challenging to start because there are so many different techniques and algorithms that you need to know before you can use them effectively. But with all this said, supervised learning is still one of the best ways to learn!

Learn supervised learning with Imarticus Learning.

Attend the E & ICT Academy deep learning Artificial Intelligence certificate program to discover how to become an AI engineer. This IIT AI ML Course will help students prepare for careers as data scientists, data analysts, machine learning engineers, and AI engineers.

Course Benefits For Learners:

  • To get practical industrial experience and prepare for a fulfilling data science career, students work on 25 real-world projects.
  • You may amaze employers and demonstrate your talents with a certificate authorized by the E & ICT Academy.
  • This machine learning course will help students land lucrative jobs in machine learning and artificial intelligence.

Contact us through the chat support system, or drive to our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad.

How Should You Learn Python For Machine Learning And Artificial Intelligence?

Posted on by Imarticus Learning
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Python is essential for those looking to get into machine learning and artificial intelligence. It is one of the easiest languages to learn and its range of dynamic semantics is unparalleled. It is easy to read and has reduced the cost of program maintenance. Artificial intelligence allows computers and software to ‘learn’ and identify patterns in order to predict outcomes and make conclusions without human interference or supervision. An example of this is the auto-reply feature on Gmail which ‘reads’ emails and predicts the reply. A machine learning engineer develops intelligent algorithms using data that has to be collected, assembled, and arranged first.
Learning Python is not just important, it is essential to machine learning and AI. There are several courses available online where you can get a Python certification and you should pick one that suits your level of expertise. If you are an absolute beginner, you should choose a course that will help you master the basics of Python. You will also learn how to use popular scientific libraries that support Python users.
The next step involves learning about Python in the scientific computing environment. As a machine learning engineer, one of your main tasks will be to work with large amounts of data. Python allows for intricate statistical modeling of said data. It works well with other programs and tools and allows for a wide range of interaction across different players.
An important area with Python learning is classification. Engineers have to be able to develop a model that classifies, identifies, and describes data classes in order to be able to classify unknown data in the future. It is one of the main forms of supervised learning and is an essential tool in your development of AI. Different types of classifier models include support vector machines, logistic regression, neural networks, and decision trees.
Regression is just as useful as classification and it also is an important form of supervised learning. However, unlike classification where there are distinct finite classes, regression works with predicting continuous numerical data.
When you are faced with data that does not have pre-defined classes, then your best tool is clustering. Simply put, clustering puts together data that are similar and separates the ones that differ. This type of data pooling is a form of unsupervised learning.
One of the best ways to learn the different aspects of Python is to learn by doing. There are several places online where you can practice your knowledge. You can also connect with other engineers and programmers and join a community to discuss and learn from others. Kaggle exercises and competitions are recommended to beginners who are looking for a challenge to flex their theoretical skills.
For those who are serious about machine learning, joining a reputed machine learning course will set you on the right path. The right machine learning training is intensive and allows you to learn hands-on with live projects. However, it is still recommended that you have some previous knowledge about Python, math, and statistics before venturing into these intensive courses.

5 Top Reasons to Learn Python

Posted on by Imarticus Learning
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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.

References:

Python Coding Tips For Beginners

Top Resources To Learn Python Online In 2022

Top Resources To Learn Python

It is Useful To Learn Python Language For Big Data

The Promises of Artificial Intelligence: Introduction

Posted on by Imarticus Learning
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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.