With so many opportunities on the horizon, a career as a Machine Learning Engineer can be both satisfying and rewarding. A good workshop, such as the one offered by KnowledgeHut, can lead you on the right path towards becoming a machine learning expert.
So what is Machine Learning? Machine learning is an application of Artificial Intelligence which trains computers and machines to predict outcomes based on examples and previous experiences, without the need of explicit programming.
Our Machine learning course will help you to solve data problems using major Machine Learning algorithms, which includes Supervised Learning, Unsupervised Learning, Reinforcement Learning and Semi-supervised Learning algorithms. It will help you to understand and learn:
The Machine Learning Course with Python by KnowledgeHut is a 48 hour, instructor-led live training sessions course, with 80 hours of MCQs and assignments. It also includes 45 hours of hands-on practical session, along with 10 live projects.
Our Machine Learning course with Python will help you get hands-on experience of the following:
Machine Learning is an application of Artificial Intelligence that allows machines and computers to learn automatically to predict outcomes from examples and experiences, without there being any need for explicit programming. As the name suggests, it gives machines and computers the ability to learn, making them similar to humans.
The concept of machine learning is quite simple. Instead of writing code, data is fed to a generic algorithm. The generic algorithm/machine will build a logic which will be based on the data provided. The provided data is termed as ‘training data’ as they are used to make decisions or predictions without any program to perform the task.
1) Stanford defines Machine Learning as:
“Machine learning is the science of getting computers to act without being explicitly programmed.”
2) Nvidia defines Machine Learning as:
“Machine Learning at its most basic is the practice of using algorithms to parse data, learn from it, and then make a determination or prediction about something in the world.”
3) McKinsey & Co. defines Machine Learning as:
“Machine learning is based on algorithms that can learn from data without relying on rules-based programming.”
4) The University of Washington defines Machine Learning as:
“Machine learning algorithms can figure out how to perform important tasks by generalizing from examples.”
5) Carnegie Mellon University defines Machine Learning as:
“The field of Machine Learning seeks to answer the question “How can we build computer systems that automatically improve with experience, and what are the fundamental laws that govern all learning processes?”
Today, algorithms of machine learning enable computers and machines to interact with humans, write and publish sport match reports, autonomously drive cars, and find terrorist suspects as well. Let’s peek through the origins of machine learning and its recent milestones.
Alan Turing created a ‘Turing Test’ in order to determine if a computer has real intelligence. A computer should fool a human into believing that it is also a human to pass the test.
The first computer learning program was written by Arthur Samuel. The program was a game of checkers. The more that the IBM computer played the game, the more it improved at the game, as it studied the winning strategies and incorporated those moves into programs.
The first neural network for computers was designed by Frank Rosenblatt. It stimulates the thought process of the human brain.
The ‘nearest neighbour’ was written. It allowed computers to use basic pattern recognition.
Explanation-Based Learning was introduced, where a computer analyses the training data and creates a general rule which it can follow by discarding the unimportant data.
The approach towards the work on machine learning changes from a knowledge-driven approach to machine-driven approach. Programs were now created for computers to analyze a large amount of data and obtain conclusions from the results.
IBM’s Deep Blue beat the world champion in a game of chess.
Geoffrey Hinton coined the term ‘deep learning’ that explained new algorithms that let the computer distinguish objects and texts in videos and images.
The Microsoft Kinect was released, which tracked 20 human features at a rate of 30 times per second. This allowed people to interact with computers via gestures and movements.
IBM’s Watson beat its human competitors at Jeopardy.
Google Brain was developed. It discovered and categorized objects similar to the way a cat does.
Google’s X Labs developed an algorithm that browsed YouTube videos and identified those videos that contained cats.
Facebook introduced DeepFace. It is an algorithm that recognizes and verifies individuals on photos.
Microsoft launched the Distributed Machine Learning Toolkit, which distributed machine learning problems across multiple computers.
An artificial intelligence algorithm by Google, AlphaGo, beat a professional player at a Chinese board game Go.
The algorithm of machine learning is trained using a training data set so that a model can be created. With the introduction of any new input data to the ML algorithm, a prediction is made based on the model.
The accuracy of the prediction is checked and if the accuracy is acceptable, the ML algorithm is deployed. For cases where accuracy is not acceptable, the Machine Learning algorithm is trained again with supplementary training data set.
There are various other factors and steps involved as well. This is just an example of the process.
Various industries work with Machine Learning technology and have recognized its value. It has helped and continues to help organisations to work in a more effective manner, as well as gain an advantage over their competitors.
Machine Learning technology is used in the financial industry due to two key reasons: to prevent fraud and to identify important insights in data. This helps them in deciding on investment opportunities, that is, helps the investors with the process of trading, as well as identify clients with high-risk profiles.
Machine learning has various sources of data that can be drawn used for insights. It also helps in detecting fraud and minimizes identity theft.
Machine Learning in the health care sector has introduced wearable devices and sensors that use data to assess a patient’s health in real time, which might lead to improved treatment or diagnosis.
There are numerous use cases for the oil and gas industry, and it continues to expand. A few of the use cases are: finding new energy sources, predicting refinery sensor failure, analyzing minerals in the ground, etc.
Websites use Machine Learning to recommend items that you might like to buy based on your purchase history.
What is the future of Machine Learning?
Machine learning has transformed various sectors of industries including retail, healthcare, finance, etc. and continues to do so in other fields as well. Based on the current trends in technology, the following are a few predictions that have been made related to the future of Machine Learning.
Understand the behavior of data as you build significant models
Learn about the various libraries offered by Python to manipulate, preprocess and visualize data
Learn about Supervised and Unsupervised Machine Learning.
Learn to use optimization techniques to find the minimum error in your machine learning model
Learn various machine learning algorithms like KNN, Decision Trees, SVM, Clustering in detail
Learn the technique to reduce the number of variables using Feature Selection and Feature Extraction
Understand Neural Network and apply them to classify image and perform sentiment analysis
Learn to use multiple learning algorithms to obtain better predictive performance
For Machine Learning, it is important to have sufficient knowledge of at least one coding language. Python being a minimalistic and intuitive coding language becomes a perfect choice for beginners.
Sign up for this comprehensive course and learn from industry experts who will handhold you through your learning journey, and earn an industry-recognized Machine Learning Certification from KnowledgeHut upon successful completion of the Machine Learning course.
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Hands-on: No hands-on
Hands-on: No hands-on
With attributes describing various aspects of residential homes, you are required to build a regression model to predict the property prices using optimization techniques like gradient descent.
This dataset classifies people described by a set of attributes as good or bad credit risks. Using logistic regression, build a model to predict good or bad customers to help the bank decide on granting loans to its customers.
Biodegradation is one of the major processes that determine the fate of chemicals in the environment. This Data set contains 41 attributes (molecular descriptors) to classify 1055 chemicals into 2 classes - biodegradable and non-biodegradable. Build Models to study the relationships between chemical structure and biodegradation of molecules and correctly classify if a chemical is biodegradable
In marketing, if you’re trying to talk to everybody, you’re not reaching anybody. This dataset has social posts of teen students. Based on this data, use K-Means clustering to group teen students into segments for targeted marketing campaigns.
Wine comes in various types. With the ingredient composition known, we can build a model to predict the Wine Quality using Decision Tree (Regression Trees).
The primary objective of Machine Learning is to enable computer systems to perform tasks like locating data, analyzing them and learning from the data without any form of external help or intervention. From the moment observations of data become available in the form of direct experiences or examples, the process of Machine Learning starts. The system looks at the provided data, tries to find patterns in them and then extrapolates these observed patterns in order to make better business decisions. It takes into account all the information and datasets available to the program or system to make its decision.
There are several methods of Machine Learning. Broadly they can be categorized in to the following two categories-
According to Angellist, there are over 250+ startups in Kolkata, such as TaxMantra, Sweethandi, Santa Delivers, Zeroinfy, etc. It is also home to several leading companies, such as Oracle, Sforce, Wipro, TCS, Cognizant, etc. In 2018, Infosys started its software development centre in Kolkata investing around Rs 100 crore in the first phase. Machine learning is helping all these companies in finding patterns and automate value extraction in many areas.
It simply works
Machines and computers have the ability to work faster than the human brain by processing a huge number of data and working out a solution faster than the human brain can. For instance, if there are millions of options, possibilities and opinions, a machine can analyze all the possibilities, systematically working out and evaluating all possibilities and finding the best outcome or conclusion.
It is used in a wide range of applications today
Machine Learning is the most practical solution to all our worldly problems and needs. It enables businesses to be more efficient by saving time, money and efforts. We can get more amount of work done with Machine Learning, making it a reliable, effective and appropriate system. Industries in Kolkata like health care, nursing, transport, governments and finance benefit from the developments in Machine Learning, making it an indispensable part of our society as of today.
Due to the social media boom, millions of data is being generated every day. At present, all companies- from startups to MNCs in Kolkata- are incorporating Machine Learning to make key decisions for their organizations. With data, big and small, being the basis of technological and industrial advancements, Machine Learning will remain an important sector for the next few decades; constantly reshaping itself to the market needs.
Listed below are the benefits of getting certified in Machine Learning-
Machine Learning is constantly evolving and developing itself everyday due to the immense amount of possibilities it offers. While one can always opt for certified courses or diplomas, self-learning ML can also be equally effective if one has the motivation to keep working forward. The few things to keep in mind are-
You can follow these steps to learn machine learning:
Follow these 5 steps:
Realize that ML is like any other creative process where as you practice more the better you get.
Companies like IBM, Wipro are looking for expert machine learning engineers in Kolkata. In order to be an ML expert, the following technical skills are mandatory to learn and imbibe in your projects-
Below are the steps to execute an ML project with Python:
Algorithms are an integral part of Machine Learning. Here’s how you can effectively learn them:
The K Nearest Neighbours (KNN) algorithm is a simplistic Machine Learning algorithm. The aim of KNN is to predict outcome of new data instance. It trains to find either the K-nearest instance of the new data instance or the K number of instances that are most similar to the new instance. The prediction or output of one of two things;
The benefits of KNN is the ease of use and simplicity. Though it uses a lot of memory to store the large dataset, it calculates only when prediction is needed.
Your intention and future goals with Machine Learning determines the necessity of learning algorithms-
Machine Learning algorithms are basically of three types:
The simplest algorithm in Machine Learning enables one to solve the simplest ML problems. According to this criteria the algorithm has to be:
K-nearest neighbor algorithm is the most simplest and widely used ML algorithms for solving basic but important real life problems. The reason for that is-
Machine Learning is the most popular and heavily used system. Thus it has a lot of tools, algorithms and models to choose from. Having an understanding of selecting the right algorithm for your problem will determine the final quality of your project.
The more you practice and implement Machine Learning algorithms the more efficient and faster will your solutions become. The process of implementation of ML algorithms are as follows:
The following are some essential topics of Machine Learning that every learner should be acquainted with:
The median salary of Machine Learning Engineer in Kolkata is ₹6,50,000/yr. The range differs from ₹3,00,000 to as high as ₹17,00,000.
The average salary of a machine learning engineer in Kolkata compared with Bangalore is ₹6,50,000/yr whereas, in Bangalore, it’s ₹8,00,000/yr.
The city of joy is one of the most developed and technologically advanced cities. As per LinkedIn, there are at least 1800 jobs available in the ML sector and the pace at which its growing, the numbers are likely to increase. It is due to the fact that industries are in need of skilled professionals who deeply understand machine learning. Reports suggest that since the sector is fairly new, it will take some amount of time before the demand is met, and even after that the growth that it has shown is a reflection of how huge this sector will be and the demand it attracts.
Being the dream work for the engineering graduates in 2018, an occupation of a Machine learning engineer in Kolkata offers different advantages, for example, -
The perks of ML engineer in Kolkata apart from the high salary are as follows -
Although there are quite many companies offering jobs to Machine Learning Engineers in Kolkata, following are the prominent companies
July 20, 2019 to August 10, 2019
Offbeat CCU, 36/F Topsia Road On EM Bypass, (Erstwhile Landmark Hotel), Kolkata, India
Summer Training Hunt
July 1, 2019 to August 1, 2019
Offbeat CCU, 36/f Topsia Road, (erstwhile Landmark Hotel), Kolkata 700 039, India
The IEEE Region 10 Symposium
June 7, 2019 to June 9, 2019
|1.||7th International Conference On Pattern Recognition And Machine Intelligence||18 August, 2017|
203, B.T. Road, Kolkata
Machine Learning is a vast field. As a result, Machine Learning Engineers have to be responsible for a lot of things including:
Companies in Kolkata are starting to understand the importance of data in making marketing decisions. This has resulted in increase in demand of Machine Learning Engineers in Kolkata. They create frameworks and systems that facilitate the data analysis process. Also, to gain insights from the data, you need to apply Machine Learning algorithms to it.
Here are the top professional groups for Machine Learning Engineers in Kolkata:
In 2019, the following ML jobs are most in demand:
Here's how you can get started on the use of Python for Machine Learning:
Below are the steps required for executing a successful Machine Learning project with Python (ML Project)-
The following steps will make it easier for you to learn using Python programming.
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Machine learning came into its own in the late 1990s, when data scientists hit upon the concept of training computers to think. Machine learning gives computers the capability to automatically learn from data without being explicitly programmed, and the capability of completing tasks on their own. This means in other words that these programs change their behaviour by learning from data. Machine learning enthusiasts are today among the most sought after professionals. Learn to build incredibly smart solutions that positively impact people’s lives, and make businesses more efficient! With Payscale putting average salaries of Machine Learning engineers at $115,034, this is definitely the space you want to be in!
By the end of this course, you would have gained knowledge on the use of machine learning techniques using Python and be able to build applications models. This will help you land lucrative jobs as a Data Scientist.
There are no restrictions but participants would benefit if they have elementary programming knowledge and familiarity with statistics.
Yes, KnowledgeHut offers this training online.
On successful completion of the course you will receive a course completion certificate issued by KnowledgeHut.
Your instructors are Machine Learning experts who have years of industry experience.
Any registration cancelled within 48 hours of the initial registration will be refunded in FULL (please note that all cancellations will incur a 5% deduction in the refunded amount due to transactional costs applicable while refunding) Refunds will be processed within 30 days of receipt of written request for refund. Kindly go through our Refund Policy for more details.
In an online classroom, students can log in at the scheduled time to a live learning environment which is led by an instructor. You can interact, communicate, view and discuss presentations, and engage with learning resources while working in groups, all in an online setting. Our instructors use an extensive set of collaboration tools and techniques which improves your online training experience.
Minimum Requirements: MAC OS or Windows with 8 GB RAM and i3 processor.
Machine Learning with Python Training in Kolkata
Kolkata, earlier known as Calcutta in English, is the capital of West Bengal. The city continues to develop in urban courses as it is being presented to industrialization, information innovation, amongst other developments. Seeing the present market situation, the city is in a profound need for programming engineers. KnowledgeHut is offering e-learning in machine learning training using python in Kolkata to enterprises for viable improvement of activities and improving efficiency. The course offers complete information on data analysis and machine learning which are perfect for programming engineers.
What is Machine Learning course all about?
This course will introduce the learner to manage large volumes of data that needs to be analyzed using the machine learning techniques in Python. Offering a host of example and real-life cases brings ease to proceed with the machine learning using python course in Kolkata while gaining real-time knowledge through an on-going project. The course will begin with a dialogue about how machine learning and data analysis using python course in Kolkata is not the same as graphic measurements with an introduction to the skit learn toolbox. Touching on the issue of data dimensionality and the errands of clustering data, this course will also help evaluate those bunches.
Benefits of the Machine Learning certification in Kolkata
Before the finish of this course, aspirants will have the capacity to distinguish the contrast between a managed and unsupervised method, recognize which procedure they have to apply for a specific dataset and need, engineer components to address that issue, and compose python code to complete an analysis. The KnowledgeHut Way The cost of the machine learning and data analysis training using python in Kolkata is very nominal. The way that the sessions are directed online using web-strategies makes it advantageous for all learners making the most of the expertise of the trained and certified workforce.