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Updated Content
Learning Paths
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Advanced Interactive
Machine Learning, a subfield of AI, allows software applications to predict the outcome through self-learning. Further, ML uses past data to learn things automatically to give accurate output. It is the ability of a machine that imitates human behavior intelligently.
HKR Training’s has brought an excellent career-building program through its Machine Learning Course. We provide different modes of learning where learners can choose their learning path. This course is designed to deliver all essential ML concepts from basics to advanced. In this course, you will learn Machine Learning basics, data processing, NLP, deep learning concepts, decision tree, and many more. You will get a clear explanation of all these concepts through an expert trainer in real time. Further, you will get thorough career guidance, doubt-clearing sessions, and practicals. So, get updated skills in real-time through HKR’s Machine Learning Training online.
To apply for the Machine Learning Training, you need to either:
The curriculum for the Machine Learning Course at HKR Trainings is designed on the recommendations of domain experts in the industry. It covers all the requirements to become an expert in Machine Learning. Please go through the below course modules to get an idea of various ML concepts.
1.1 Need of Machine Learning
1.2 Introduction to Machine Learning
1.3 Types of Machine Learning
1.4 Machine Learning with Python
1.5 The applications of Machine Learning
2.1 Introduction to Data Exploration
2.2 Data Exploration Techniques
2.3 Seaborn
2.4 Data Wrangling
2.5 Missing values in a dataset
2.6 Outlier values in a dataset
2.7 Data Manipulation
2.8 Different types of Joins
2.9 Typecasting
3.1 Understanding the Algorithm
3.2 Supervised Learning Flow
3.3 Types of Supervised Learning
3.4 Types of Classification Algorithms
3.5 Types of Regression Algorithms
3.6 Accuracy Metrics
3.7 Cost Function
3.8 Evaluating Coefficients
3.9 Challenges in Prediction
4.1 Regression
4.2 Factor Analysis Process
4.3 Principal Component Analysis (PCA)
4.4 First Principal component
4.5 Eigen values and PCA
4.6 Feature Reduction
4.7 Linear Discriminant Analysis
4.8 Maximum Seperate Line
5.1 Introduction to regression
5.2 Simple linear regression
5.3 Multiple linear regression and assumptions in linear regression
5.4 Math behind linear regression
6.1 Introduction to classification
6.2 Linear regression vs logistic regression
6.3 Math behind logistic regression
7.1 Introduction to tree-based classification
7.2 Understanding a decision tree
7.3 Understanding the concepts of information gain
7.4 Introduction to ensemble techniques
8.1 Introduction to probabilistic classifiers
8.2 Understanding Naïve Bayes and math behind the Bayes theorem
8.3 Understanding a support vector machine (SVM)
8.4 Kernel functions in SVM and math behind SVM
9.1 Types of unsupervised learning
9.2 Introduction to k-means clustering
9.3 Math behind k-means
9.4 Dimensionality reduction with PCA
10.1 Introduction to Natural Language Processing (NLP)
10.2 Introduction to text mining
10.3 Importance and applications of text mining
10.4 How NLP works with text mining
10.5 Writing and reading to word files
10.6 Language Toolkit (NLTK) environment
10.7 Text mining: Its cleaning, pre-processing, and text classification
11.1 Introduction to Deep Learning with neural networks
11.2 Biological neural networks vs artificial neural networks
11.3 Understanding perception learning algorithm
11.4 Introduction to Deep Learning frameworks
11.5 TensorFlow constants, variables, and place-holders
12.1 What is a time series? Its techniques and applications
12.2 Time series components
12.3 Moving average, smoothing techniques, and exponential smoothing
12.4 Univariate time series models
12.5 Multivariate time series analysis
12.6 ARIMA model and time series in Python
12.7 Sentiment analysis in Python (Twitter sentiment analysis) and text analysis
13.1 Overview of Ensemble Learning
13.2 Working of AdaBoost
13.3 AdaBoost Algorithm and Flowchart
13.4 Gradient Boosting
13.5 XGBoost
13.6 Model Selection
13.7 Common Splitting Strategies
13.8 Cross Validation
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Mercedes-Benz wants to shorten the time models spend on its test-bench, thus reducing a car’s time to market. Build and opti.....mize a Machine Learning algorithm to solve this problem. Read more
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HKR Trainings offers interactive Machine Learning Training to aspirants who are willing to build a career in this field. This course will provide you with in-depth skills in various Machine Learning concepts. Further, HKR Trainings will give you all the resources to learn Machine Learning to get more job opportunities.
To start with the Machine Learning Training, you need to click on the “Enroll Now” option given on the website. You can also fill up the Registration form with the required details and submit it to us to get a callback, or you can connect with our customer support team in this regard to get course details.
Machine Learning is an in-demand course to build a solid career in the IT sector. For this, one needs to be excellent in the various concepts of ML, starting from the basics. If you’re a beginner and want to learn Machine Learning, you can enroll in HKR Trainings, to begin with. Also, our interactive sessions, course materials, and videos will help you to learn well.
Anyone who is an undergraduate or graduate with a science background or has studied mathematics, statistics, technology, etc., can take the Machine Learning course. Having these skills will be an added advantage to learning ML.
After completing the Machine Learning Course by attending all the classes and submitting the assignments and project work, HKR Trainings will issue the course completion certificate. You can add this certificate to your resume/profile to get more job opportunities and share it across social channels like LinkedIn.
At HKR Trainings, industry-experienced trainers with domain expertise will deliver the Machine Learning Course. There will be interactive live sessions with real-time scenarios to help you gain expert ML skills.
Machine Learning Certification will differentiate you from your peers who need to be certified. Also, this certification will boost your confidence and enhance your existing career.
Right from the first day of your Machine Learning Course, our trainers will ensure that you understand all the concepts well. They will help you reach your dream job with the right skills. Further, you will get assistance in resume preparation and mock interview sessions, which will help you to crack the real-time interviews. Moreover, we are connected with some corporate companies to provide you with a job. So, we will forward your resume to them whenever there are job opportunities.
Every class is recorded. If you have missed your class, you can learn those concepts from the recorded sessions of the missed class. So, No worries!
Yes! Right from the first day of your Machine learning training, our trainers make sure that you understand all the concepts and provide you with complete guidance to reach your dream job. And when you complete your course, we will also assist you in your resume preparation which will give you the confidence to clear your interview. Moreover, We are also tied up with some corporate companies. So when they have a requirement, we send your profiles to them.
At HKR, we provide a free demo session for training seekers so they can check our quality and method of education before they enroll.
Our trainers are real-time experts who are presently working on a particular platform on which they are providing training.
You can contact our customer care number if your query does not belong to any of the questions we have addressed in this article. We will get back to you as soon as possible.
HKR Trainings assures that the learners get a quality course from our trainers. You (the learners) will have lifetime access to recorded sessions. So in case of any doubts, you can watch these recorded sessions or even can ask your trainers to clarify them. Moreover, you will also be working on a real-time project which will help you understand the concepts more clearly. So there is no question of not being satisfied.
We will accept the Refund requests within three days of the course purchase without raising questions in case of Instructor-led training. We do not accept the cancellation requests or provide any refund for the Self-paced Course once you have purchased it.
In India, the salary for a Machine Learning Engineer is in between ₹ 3.5 Lakhs and ₹ 21.1 Lakhs.
Python is the best fit for Machine learning. It has access to a number of libraries. Moreover it is a very easy language to use.
Of Course Yes! Machine learning is a good career option. Machine learning engineer is the top most job in terms of job openings, salary and demand.
You need to have in depth knowledge of some of the mathematical and computer science concepts. You even need a lot of attention to find the inefficiencies in the algorithms and optimize them. These are some of the aspects that make Machine learning hard.
Machine learning is referred to as a branch of computer science and artificial intelligence in which the primary focus is on the usage of the data and the algorithms to help the humans learn and improve the efficiency. In fact, Machine learning is considered as one of the crucial components in the data science field and makes use of the algorithms and statistical methods in order to make predictions and uncover the key insights.
As Machine learning is a branch of artificial intelligence, it has the capability to provide the systems with the ability of learning things automatically and gain experience without any explicit programming. The primary focus of machine learning is to develop the computer programs which are capable of accessing and also use it for learning.
Yes! Generally Machine learning is built on mathematical prerequisites. Machine learning will be interesting when you realize why math is used.
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