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Transformational advancements in technology in today’s world are making it possible for data scientists to develop machines that think for themselves. Based on complex algorithms that can glean information from data, today’s computers can use neural networks to mimic human brains, and make informed decisions based on the most likely scenarios. The immense possibilities that machine learning can unlock are fascinating, and with data exploding across all fields, it appears that in the near future Machine Learning will be the only viable alternative simply because there is nothing quite like it!
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 master this science and understand Machine Learning algorithms, which include 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 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 to identify clients with high-risk profiles.
Machine learning is finding varied uses in running government initiatives. It helps in detecting fraud and minimizes identity theft. It’s also used to filter and identify citizen data.
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.
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
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).
Machine Learning is the field of science that uses the concepts of Artificial Intelligence to help the systems get the ability to learn, perform, and improve the given set of tasks. These systems do not require any human help or reprogramming. The area of Machine Learning focuses on developing computer programs and systems that will be able to access data, analyze and learn all on their own, without any human intervention.
When it comes to Machine learning, the processes that are used include observing the available data using examples or direct experience to derive information. The systems and programs then analyze this data to decipher the pattern. To help in making better decisions in the future, these observed patterns need to be extrapolated. All of this is done just on the basis of the datasets and the examples provided to the computer system.
There are several major algorithms in the field of Machine Learning that can be categorized into the following categories-
1. Supervised Machine Learning Algorithms
The supervised machine learning algorithms use labeled examples to take the information taken from the past data and apply them to the new data for predicting events in the future. This is how the whole process goes down:
2. Unsupervised Machine Learning Algorithms
The Unsupervised Machine Learning Algorithms are used when the data that is provided to the system for the learning and training of the system is unlabelled and unclassified. Here is how the unsupervised machine learning algorithms work:
The vibrant city Delhi bustles with some of the best companies to work for and is home to several leading companies, such as Gaana, OLX, Indiamart, Lava, Samsung, etc. All these companies are looking for expert ML engineers to help them designing and developing Machine Learning Systems.
The basic concept of Machine learning revolves around computers and data. 90% of the data on the internet has been created since 2016, according to an IBM Marketing Cloud study. A huge amount of this data is taken, analyzed and used in training systems to solve problems and obtain the best possible outcome for a problem. Basically, it solves a problem without us even knowing that it exists. It has a particular approach to a problem that helps in solving it.
It is no surprise that machines are faster than human problems. They can get a solution faster than we can understand the problem. For example, if there are a million options for a problem, a machine will be able to systematically resolve, evaluate, and work out all the options to give you the best possible result with the help of the right algorithm.
Machine Learning has been used in several real-world applications. It has offered a solution to several problems. It helps save time, money and efforts by driving business. People are able to use Machine Learning to get the work done in a more appropriate, effective, and efficient manner. Many industries have started to incorporate Machine Learning and are benefitting from it. Some examples include transport, nursing, health care, banking, government institutions, finance, customer service, etc.
Tons of data is generated every day. And now that we have started using data for decision making, it is changing everything we know. From small startups to large MNCs in Delhi, all the companies are trying to use the data for their own benefits. This data-driven decision making is reshaping the business and will continue to do so in the near future.
The state of Machine Learning in companies and in your daily life
Machine Learning is a new field of the tech world and still, a lot of research is required to harness the field. Over the years, tech experts have been trying to find ways to make use of Machine Learning. Social Media feeds shown by Facebook and Instagram, Product recommendations on Amazon, detection of financial fraud in banks, surge pricing in uber are some of the many functionalities of the Machine Learning algorithms. Day by day these systems are able to function with less human interference.
In some way or another, knowingly or unknowingly, every person is using one or the other product of Machine learning. It has become an inevitable part of every profession, especially the ones involved in the field of Data Science and Information Technology.
Here are some of the benefits of Machine Learning that you should know -
In a report published by Tractica, in the year 2016, the services driven by Artificial Intelligence were found to be of $1.9 billion worth. By the year 2025, this number is expected to increase to reach about $19.9 billion. Every corporation in the world is trying to use Machine Learning in their decision-making process. The domains of Machine Learning and Artificial Intelligence are expanding to every industry. This has led to more and better career opportunities in the present as well as future.
Payscale published a report in which it stated that a machine learning engineer can earn up to an average of about Rs. 7,25,000 per year in Delhi.
Even though Machine Learning is in such a huge demand, there are not enough qualified Machine Learning engineers available. This has led to a huge gap between demand and availability. The Chief Information Officers (CIOs) of some huge corporations in the world have pointed out this skill gap. However, this also means that if you have Machine learning skills, not only will you be in demand but you would also be paid quite handsomely. And this demand is only going to increase in the future. There are several companies in Delhi that are hiring Machine Learning engineer including Genpact, Boston Consulting Group, Adobe, Accenture, American Express, dunnhumby, Ericsson-Worldwide, Amazon, VMware, Expedia Group, Oracle, Orange, Saavn, Telesoft Technologies, Hike, BlackRock, etc.
Most of the industries around the world are dealing with more data that they can handle. And this production of data is only going to increase in the future. Companies are quick to get the benefits of data analysis. Through this, not only are they working competently and efficiently but they are also getting ahead of their competitors.
If you want to work in the field of Machine Learning, the time is right since all the fields are looking for Machine Learning engineers. These fields include healthcare, finance, oil and gas, transportation, and government agencies.
Machine learning is a huge and diverse field that is expanding every day. There are a number of certification courses in Delhi that will help you learn Machine Learning including:
However, you can also learn the field through self-learning as long as you are motivated and keep the following in mind:
Below are the steps you can follow:
What is important is that you solve machine learning problems daily to polish your skills and incorporate an out-of-the-box thinking approach to a simple solution.
One of the best ways to get started with Machine Learning is to connect with other professionals. Here is a list of Machine Learning meetups in Delhi where you can connect with other Machine Learning Engineers:
If you are an absolute beginner, here is a 5 step process to help you get started with Machine Learning-
In Delhi, companies like cube26, Pinnacle Digital Analytics, GoPaisa, Fitfyles, Sentieo, Ank Aha, Bobble App, iNICU Medical Private Limited, Saffron Consultancy Services, Wingify Software Pvt Ltd, Secninjaz, Fintech, Sumo Logic, Mobileum, ByteDance, Genpact, etc. are looking for Machine Learning professionals with suitable experience that will help the organization make crucial marketing decision.
If you want to become a successful Machine Learning engineer working on developing successful machine learning projects, you need to have the following technical skill sets:
The steps required for executing a successful Machine Learning project with Python are mentioned below:
Once you have followed all the above-mentioned steps, you would have created and executed the machine learning project successfully.
Algorithms are one of the most integral parts of the Machine Learning field. It is very important that you completely understand the concepts of Machine Learning algorithms. Here is how you can do that-
When you are a beginner in the field of Machine Learning, you need to understand the concept of K Nearest Neighbors algorithm. It is a simple and uncomplicated algorithm that will help you get started in the field of machine learning. The aim of the problem is to predict the class of a data point from a totally multiclass dataset using the K Nearest Neighbor algorithm.
It is one of the simplest machine learning algorithms. When it comes to classification problems or problems with a huge number of regressions, K Nearest Neighbor algorithm has proven to be very useful and successful. It can be used for image analysis as well as character recognition.
Whether you need to learn machine learning algorithms or not depends on what you want to do with machine learning.
The Machine Learning Algorithms can be categorized into the following 3 categories -
The simple machine learning algorithms can be used to solve the simple ML problems. An algorithm can be defined as simple if it has the following characteristics:
Now, based on the above-mentioned criteria, the simplest algorithm in the field of machine learning is the k-nearest neighbor algorithm. Here are some reasons what makes the kNN algorithm the simplest machine learning algorithm and is still extensively used for solving basic, but real-life problems:
When it comes to machine learning, there are a lot of algorithms, models, and tools that you can select from. But before you select an algorithm that is the backbone of your project, you need to keep certain things in mind, including the following:
To design and implement a machine learning algorithm using python, you need to follow the below mentioned steps:
All the basic concepts of machine learning are required for you to work on a machine learning project. Here we have narrowed down the most essential topics of machine learning that one needs to master to get thoroughly acquainted with machine learning:
Advantages of decision tree methods:
Some of the advantages of this algorithm include:
The median salary of Machine Learning Engineer in Delhi is ₹8,75,635/yr. The Range differs from ₹3,76,000 to as high as ₹11,60,000
The average salary of a machine learning engineer in Delhi compared with Bangalore is ₹8,75,635/yr whereas, in Bangalore, it’s ₹8,00,000/yr.
Cities near Delhi have reported an average salary of ₹6,50,000/yr for machine learning engineers. Although most of these cities have an average less than that of Delhi, Gurgaon has a high average of ₹10,10,000/yr.
According to a recent study done by Research and Markets, the global machine learning market is anticipated to grow from $1.4B in 2017 to $8.8B by 2022. It is also revealed that ML patents have seen a huge development of about 344% in the last 3 years. The majority of these licenses were under colossal tech organizations like Microsoft and Facebook who additionally have a base in New Delhi and are continually hoping to update themselves. Besides, New Delhi is itself, home to a few top tech organizations. These companies are looking for talented engineers who can utilize machine learning to deliver the best outcomes. So, yes, machine learning engineers are in high demand in Delhi.
Having the most attractive job among engineers in the 'National Capital of India' has its very own advantages
Delhi offers endless opportunities due to the fact that it gives a massive exposure to all kinds of technology. Moreover, this allows the engineer to figure out where to go, what to use and how to deliver an apt result. So not only are you getting high package salaries, but there are added bonus, acknowledgement, networks and career stability.
Although there are quite many companies offering jobs to Machine Learning Engineers in Delhi, following are the prominent companies -
International Conference on Artificial Intelligence, Machine Learning and Big Data Engineering (ICAIMLBDE)
June 23rd, 2019
Hotel Suncourt Corporate, 6A/67, WEA, Channa Market, Karol Bagh, New Delhi,110005
International Conference on Robotics, Machine Learning and Artificial Intelligence (ICRMLAI)
June 23rd, 2019
Hotel Suncourt Corporate, 6A/67, WEA, Channa Market, Karol Bagh, New Delhi,110005
International Conference on Data Management, Analytics and Innovation - ICDMAI 2020
17-19 January, 2020
United Services Institute (USI) Rao Tula Ram Marg, Shankar Vihar, New Delhi, 110010
|S.No||Categories||Registration Fee For Author outside of India|
Registration Fee For Author of India
|300 USD||9200 INR|
|2.||Authors (Student M.tech/Ph.D.)||250 USD||7200 INR|
|3.||Authors (B.Tech)||200 USD||6200 INR|
|4.||Listeners:||70 USD||3000 INR|
|5.||Additional Paper (s)**||100 USD||5000 INR|
|6.||Additional Page||50 USD / One Page||1500 INR / One Page|
|7.||Extra Proceeding||100 USD|
7. Who are the major sponsors:
Registration Fee For Author outside of India
|Registration Fee For Author of India|
|1.||Authors (Academician/Practitioner)||250 USD||9000 INR|
|2.||Scholars (Ph.D./Post Doc.)||200 USD||7000 INR|
|3.||Student(All Masters degree holders)||180 USD||6000 INR|
|4.||Student(All Bachelors degree holders)||150 USD||5000 INR|
7. Who are the major sponsors:
The responsibilities of a Machine Learning Engineer include:
Delhi is not only home to several leading tech companies but there are more than 5000 startups in the capital, including Snapdeal, Limetray, Hike, Ecom, Lenskart, etc. Delhi has been able to generate $2.8 Billion of funding during the first half of the previous financial year. It is a great time for being a Machine Learning Engineer in Delhi. As more and more companies these days are adopting artificial intelligence technologies, Machine learning engineers are in high demand.
Some of the ML job roles in demand are:
The average salary for a Data Scientist with Machine Learning skills in New Delhi, Delhi is Rs 725,000.
Here's how you can start using Python for mastering Machine Learning:
The top essential Python libraries used to implement machine learning with python include:
Here we have compiled the steps required to execute a successful machine learning project using python:
Here are the 6 best tips to learn python programming as a beginner:
Thanks to its big, open-source community; Python has several libraries for you to play with. Here are the best Python libraries essential for Machine Learning:
Overall, the training session at KnowledgeHut was a great experience. I learnt many things. I especially appreciate the fact that KnowledgeHut offers so many modes of learning and I was able to choose what suited me best. My trainer covered all the topics with live examples. I'm glad that I invested in this training.
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Knowledgehut is the best platform to gather new skills. Customer support here is very responsive. The trainer was very well experienced and helped me in clearing the doubts clearly with examples.
The course materials were designed very well with all the instructions. The training session gave me a lot of exposure to industry relevant topics and helped me grow in my career.
I really enjoyed the training session and am extremely satisfied. All my doubts on the topics were cleared with live examples. KnowledgeHut has got the best trainers in the education industry. Overall the session was a great experience.
The workshop was practical with lots of hands on examples which has given me the confidence to do better in my job. I learned many things in that session with live examples. The study materials are relevant and easy to understand and have been a really good support. I also liked the way the customer support team addressed every issue.
The workshop held at KnowledgeHut last week was very interesting. I have never come across such workshops in my career. The course materials were designed very well with all the instructions were precise and comprehenisve. Thanks to KnowledgeHut. Looking forward to more such workshops.
This is a great course to invest in. The trainers are experienced, conduct the sessions with enthusiasm and ensure that participants are well prepared for the industry. I would like to thank my trainer for his guidance.
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.
Learn Machine Learning with Python in Delhi
Delhi is a delightful tapestry of medieval monuments, marvelous Mughal architecture, and busy old world bazaars that exist harmoniously alongside high rises and glitzy modern malls. As the capital city of India, in Delhi rests the seat of political and economic power. Delhi and the adjacent National Capital Region are the largest business and commercial center of northern India. This region has attracted both the best companies as well as great talent that come to the capital city looking to grow and prosper. However, the competition is tough and companies are spoilt for choice and will recruit only trained and certified candidates. As a result, candidates especially developers will benefit from pursuing e-learning programs in data analysis using Python course in Delhi. Attaining this certification will ensure that they remain highly employable and experience the rewards of career advancement. Made available by KnowledgeHut, this training is via online classes where programmers are given an exhaustive overview of both, theory and practical aspects of the subject. Python finds industry-wide acceptance and is a preferred language of many developers. Easy to learn and use, several organizations use this tool to build applications. However, to build a game or a web app, programmers need to enroll for formal training like the machine learning using Python course in Delhi to get a full grasp on the subject and have the ability to create effective applications or products.
Delhi is a central hub of technology and innovation, hosting both well established and many next-gen start-ups in the tech space. Pursuing online training for machine learning with Python is a good way to ensure that IT professionals have a chance at exploring great prospects in Information Technology domain, and many other such areas where such expertise is required. New Alternative Python is a powerful programming language used for creating several different applications. An open source language, this has a huge community that has created effective tools within the Python framework and over the last few years? specific tools have been developed for data science and analysis. Easy to install and use, this language can be deployed for application of any scale and size. It enables clear programs and emphasizes clarity of syntax along with easy comprehension and readability.
Keeping Ahead of the Curve
Taking up the Machine Learning with Python Course in Delhi is a remarkable way to stay ahead of the curve because this program ensures they have enhanced employment along with the potential of higher income. Developers can join the KnowledgeHut online classes, led by industry veterans who make sure that there is seamless knowledge transfer and the students build capability in this space.
KnowledgeHut Empowers You
The machine learning training using Python is available at a great price in Delhi. The online modules, conducted by KnowledgeHut provide superior training enabling developers to become highly proficient and can ace an exam with absolute ease.