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.
3 Months FREE Access to all our E-learning courses when you buy any course with us
Interact with instructors in real-time— listen, learn, question and apply. Our instructors are industry experts and deliver hands-on learning.
Our courseware is always current and updated with the latest tech advancements. Stay globally relevant and empower yourself with the training.
Learn theory backed by practical case studies, exercises and coding practice. Get skills and knowledge that can be effectively applied.
Learn from the best in the field. Our mentors are all experienced professionals in the fields they teach.
Learn concepts from scratch, and advance your learning through step-by-step guidance on tools and techniques.
Get reviews and feedback on your final projects from professional developers.
Hands-on: No hands-on
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).
Overall, the training session at KnowledgeHut was a great experience. Learnt many things, it is the best training institution which I believe. My trainer covered all the topics with live examples. Really, the training session was worth spending.
Knowledgehut is the best training institution which I believe. The advanced concepts and tasks during the course given by the trainer helped me to step up in my career. He used to ask feedback every time and clear all the doubts.
I am glad to have attended KnowledgeHut’s training program. Really I should thank my friend for referring me here. I was impressed with the trainer, explained advanced concepts deeply with better examples. Everything was well organized. I would like to refer some of their courses to my peers as well.
I liked the way KnowledgeHut framed the course structure. The trainer was really helpful and completed the syllabus on time and also provided live examples. KnowledgeHut has got the best trainers in the education industry. Overall the session was a great experience.
KnowledgeHut has all the excellent instructors. The training session gave me a lot of exposure and various opportunities and helped me in growing my career. Trainer really was helpful and completed the syllabus covering each and every concepts with examples on time.
Knowledgehut is the best training provider which I believe. They have the best trainers in the education industry. Highly knowledgeable trainers have covered all the topics with live examples. Overall the training session was a great experience.
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. Thanks to KnowledgeHut, looking forward to more such workshops.
I would like to extend my appreciation for the support given throughout the training. My trainer was very knowledgeable and liked the way of teaching. The hands-on sessions helped us understand the concepts thoroughly. Thanks to Knowledgehut.
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 Bangalore
Join our 5-day intensive machine learning training with python in Bangalore and get hands-on expertise on the use and benefits of Python programming language. This Data analysis and machine learning class training in Bangalore have been designed to give maximum learning benefit to beginners who want to get proficient in Python programming language. On joining this course you will receive 40 hours of intensive training from trained and certified experts, downloadable course book and course completion certificate issued by KnowledgeHut. You will get a chance to get your hands dirty with our intensive lab exercises that will teach you the full functionality and working of Python. By the end of this course, you would have mastered Python to build your own Python packages.
For busy professionals who are unable to attend our classroom training, we bring online classes that represent e-learning at its best and will give you all the advantages of a regular course.
Machine Learning with Python certification in Bangalore
So many programming languages are now being used and each has its own advantages and disadvantages. But Python has stood out among all others because of the numerous advantages it offers. First of all, it does away with many of the redundancies and repetitions in code. Python is fairly easy to master and has a syntax that is clear and readable. Also, its object-oriented nature allows code to be re-used. Its other advantages are that it is free, is cross-platform so can run on major operating systems like Windows, Linux and Mac is widely supported by a strong community of developers and is extensible and safe.
All these make it a very likable programming language and many organizations like their programs to be built on Python. There is a huge demand for Python professionals and hence KnowledgeHut has created this machine learning certification training in Bangalore on successful completion of which you will receive the machine learning certification in Bangalore.
Our machine learning with python course in Bangalore will teach you advanced data structures and algorithms, using libraries such as SciPy, NumPy, and Pandas to create data frames, grouping, processing data and performing numerical and scientific analysis and creating classifiers and clusters. This is a complete workshop and at the end of this course, you would have completely mastered Python.
Bangalore is a great city and has created a reputation for itself as being India’s IT capital. Python programmers are much in demand and the right skills can have a huge impact on your career. Join today for great coaching and great classroom environment