Machine Learning Training in Chennai

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Machine Learning Training in Chennai

KaaShiv Infotech offers, machine learning training in chennai . Our, machine learning course in chennai – provides you an in-depth knowledge on ML Programming.  This traning enables the students to understand and learn the current trend in the job market. Students will  prefer ” machine learning training ” to  build their profile for their jobs & also for their higher studies. Our company provides both machine learning offline and machine learning online internship that imparts technical and programming skills below list of ML areas,

  1. Machine Learning Basics–  Machine Learning Programming, Python Programming, Python Installation
  2. Linear Regression with One Variable, Multiple Variables & Python functions –  Python User defined/system functions/string manipulations
  3. Python Machine Learning Machine learning with Python Programming , Algorithms& its implementation
  4. Preprocessing of Research Data  – Delete Missing values, Detecting, Handling – Outliers, Preprocessing Categorical Features , Library Data
  5. Python dictionary/Logistic Regression/Python Sets  – Python dictionary Programming/Python Sets/Arrays / Operators
  6. Advanced Machine Learning Concepts  – Advanced Concept of ML,  (NLP), Tensorflow overview and Deep Learning Intro
  7. Machine Learning Projects  – Implementing machine learning programming

Highlights of our company

  • Run by 10 Years Awarded Microsoft Most Valuable Professional
  • Common Wealth Bank Recognized Leading Rising Star Award Winner
  • Google Recognized Experts
  • Cisco Recognized Certified Experts
Machine Learning Course

Why our company provides, Machine Learning Training in Chennai

The Course curriculum for, machine learning training course – is carefully researched and prepared by professionals from MNC to meet the demands expected in the current IT industries. After completing internship in Chennai at KaaShiv Infotech, students will be familiar with the entire Machine learning concepts with python, Data science with python, Implementing – Machine Learning Projects . Below are some of the insights of our  programme, ai and machine learning certification in chennai ,

Gain a new perspective on your student life
Discover New And Hidden Talent
Real-time project development and Technology Training
Bolstering your CV
100% Practical Technology training
Earn academic credit & fulfil academic goals
Real Life Experience and Exposure
After completion, Course Materials will be provided.
Guidance in creating R & D projects

Trainers to train you

Our, best machine learning training in india – Trainers are real-time IT experts and professionals worked in machine learning programming from leading MNCs like

  • TCS,
  • HCL,
  • Infosys,
  • Cognizant,
  • Wipro
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Machine learning Training opportunities

There is a demand for machine learning professionals both in India and across the world. As per reports, 70,000+ data science jobs are vacant due to lack of talent.

  • Lack of good relevant education: Most colleges are lagging in teaching machine learning and technology subjects. The education isn’t in-sync with what the business needs
  • There are few Machine Learning Training in Chennai opportunities out there, resulting in fast growth of self-taught and uncertified machine learning professionals
  • Lower levels of fluency in coding: Most self-taught machine learning individuals learn by only watching videos, resulting in small practice of hands-on ML model building

As a result, you end up with a very large population of uncertified professionals challenging the high-paying machine learning jobs and Projects.

Why Machine Learning Training is important ?

  • This Machine Learning Training in Chennai gives you a clue of meaningful industry experience, while touching upon all the machine learning techniques and algorithms necessary in the business today
  • This Machine Learning training offers an in-depth outline of Machine Learning areas including working with real-time data, developing algorithms using supervised & unsupervised learning, regression, classification, and time series modelling.

Below are some of the, machine learning training jobs :

  • Machine Learning Developer
  • Machine Learning – Technical Director
  • PYTHON Application Designer / Internet of Things
  • Research Analyst
  • Data Analyst
  • Data Scientist

What is Machine Learning ? - Basic Introduction on Machine Learning

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Machine Learning Course

Machine Learning Course Training to the Students

Learn and Implement
70 to 400 Concepts Covering 9 Technologies
+ 3 to 4 Projects

Machine Learning Training in Chennai Course Structure

  • Machine Learning Course – Duration: Week Day / Week End – Any Day Any Time – Students can come and study
  • Training hours: 50hrs
  • Software & other tools installation Guidance
  • Hardware support
  • Machine Learning Course Materials / Machine Learning Project Report creation
  • KaaShiv Infotech is top under,  machine learning training india ,  based 1  real time projects.
  • Certificates will  be given
    • Course Completion Certificate
    • Industrial exposure certificate
    • + ( Achievement Certificate for best performers and Researchers )
  • Free Machine Learning Training in Chennai –  Real time project – After 6 months of regular Paid Internship, Internship becomes free + For best interns Stipend will be provided + Best Interns will be offered Job too.
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Machine learning training near me

100% Practical – Live HandsOn  – Machine learning training chennai

Topic 1 : Machine Learning  – Introduction
What is Machine Learning , Linear Regression Theory , Multiple Linear Regression , Decision Tree , Naive Bayes classifiers, Support Vector Machines , Association Rule, Neural Networks , Random Forest, Recommendation Engine
Topic 2 : Python Programming – What is Python
History of Technology , Evolution of Programming Languages , What is python , History of Python , Why Python , Where Python used for? , Big Companies Using python , Tools and Frameworks In Python , How Python code works , Python for .Net and Java , DOWNLOAD & INSTALL PYTHON , Domain Vs Tools in Python , Install Python ,Python Tool – How to work
Topic 3 : Python – Python Advanced
What is Class & Object , What is Constructor , Whsat is Inheritance , What is self method , Try except , Raise exception
Topic 4 : Machine Learning – Algorithms
Popular Machine Learning Algorithms, Clustering, Classification and Regression , Supervised vs Unsupervised Learning
Topic 5 : Choice of – Machine Learning
Model Evaluation and Model Selection
Topic 6 : Python  – Machine Learning
Creating a Data Frame , Transform Values to Numbers , Data Mappers , Null Finding , Null Mapping to Mean Value , Null Mapping to Constant Value , Accessing Inbuilt Data Sets , Finding Outlier Data , Filter Missing Values , Feature Selection
Topic 7 : Preparation of – DataSets
Create IRis Datasets using scikit-learn , Simulated data for Classification , Simulated data for Clustering , Simulated data for regression
Topic 8 : Preprocessing of – Research Data
Delete Missing values , Detecting Outliers, Handling Outliers, Preprocessing Categorical Features , Preprocessing Library Data
Topic 9 : Feature Engineering in – Machine Learning 
Feature Extraction with PCA, Dimensionality Reduction with PCA, Selecting best components For LDA
Topic 10 : Feature Selection in – Machine Learning 
Variance Thresholding Binary Features , Variance Thresholding For Feature Selection
Topic 11 : Machine Learning  – Supervised Learning
Simple and Multiple Linear Regression , Logistic Regression, KNN ,Random Forest Classifier, Random Forest Regression, Decision Tree Classifier, Decision Tree Regression, Naïve Bayes Classifier, Support Vector Machine (SVM), Artificial Neural Network (ANN), Basic ANN network for regression and classification
Topic 12 : Machine Learning  – Unsupervised Learning
K-means Clustering, Agglomerative Clustering
Topic 13 : Advanced – Machine Learning Concepts
Advanced Concept of Machine Learning , Natural Language Processing (NLP), Tensorflow overview and Deep Learning Intro
Topic 14 : Machine Learning  – Natural Language Processing (NLP)
Text Processing with Vectorization, Sentiment analysis with TextBlob
Topic 15 : Machine Learning  – Tensorflow overview and Deep Learning Intro
Tensorflow work flow demo and intro to deep learning

+ Course Completion Certificate

+ Free Industrial exposure certificate + (Achievement certificate for best performers) + 1 Machine Learning Projects

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How to get - free machine learning training

Apply for Course - Contact Us

Thanks for choosing our 100% Practical interactive, online machine learning training . As an Intern, you will get high end technological knowledge for sure. Welcome to KaaShiv Infotech, best training company to provide, machine learning training in chennai . Opening for Machine Learning course for the year , machine learning course 2021 , machine learning course 2022 , machine learning course 2023 is available to apply

Contact Number / Whatsapp Number

Mobile 1 : 7667662428
Mobile 2 : 7667664842
Mobile 3 : 9840678906
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Machine Learning Online Internship

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More about our Company

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Our, best machine learning training institute - Training Youtube Channels –

Our Technology Channel :

https://www.youtube.com/channel/UC2MYZHG8a56u4REI2RedtRA

 

Our Subject Channel : 

https://www.youtube.com/channel/UC9dcBYLL-ZGTy7ml8YMTlag/videos

 

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Check our ( Intern )Students Feedback :

Inplant training in chennai for Machine Learning – Feedback – https://www.kaashivinfotech.com/inplant-training-feedback

 

Machine Learning Course – Feedback  – interns for machine learning students

 

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1. Machine learning training report will be provided after the completion of the programme.

2. Regular tech updates to the students.

3. Free course Projects given

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1. Industry Recognized, Course certificate will be given.

2. Certificates will be given ( Course Completion Certificate & Industrial exposure certificate ) + (Achievement certificate for best performers)

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2 day / 3/ 4 / 5 / 10, 20 days or 1 month to 6 Months ( Any Number of Days – Based on student preferences)

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Machine Learning Training in Chennai for freshers

  • This training can be done by the freshers to build their career. This programme will provide a clear baseline for entry level engineers to  enter into the IT industry.
  • Before entering into the companies, doing an course will give you more clarity in the programming field.
  • Machine Learning training for students – Kaashiv Infotech recommends all department students, fresher and even school students to take up this training and build their career.

Machine learning Training in Chennai for beginners

  • This training can be done by the begineers to build their career. This programme will provide a clear baseline for entry level engineers to  enter into the IT industry.
  • Machine Learning training in chennai , kaashiv recommends all department students, fresher and even school students to take up this training and build their career.
  • training for ML programmers – Learning the programming techniques and getting ideas to do machine learning projects enables the programmer to be well versed in technology
  • Enables the machine training developers to learn basic programming, logical skills, analytical skills and advanced programs involving machine learning with python and data science with python.

summer Machine Learning Training in Chennai

  • Kaashiv Infotech offers machine learning summer training for engineering students imparting basic to advanced level of knowledge.
  • It is the best summer training institute including of a team of best and industry experience professionals as trainers for machine learning training program.
  • This further makes sure that the students are in safer hands and under the best mentorship to enhance their skills.
  • The Machine learning summer training opens up huge career options for the students and is ideal for 1st/2nd/3rd/4th year engineering students and aims at increasing their prospects and enhancing skills in order to change themselves into industry specialists.

winter Machine Learning Training in Chennai

  • Training can be done by diploma studying students , engineering students or freshers and arts college students too.
  • Students can prefer the training in the winter holidays too. Doing meaningful learning in the holidays is the best and first step towards the vision of success. The reason is, your career is getting enhanced and Practical knowledge with programming skills carves the machine learning interns towards cutting edge technologies.

Machine Learning Course in Chennai

  • This Machine Learning training will Covers the entire Python Libraries Such as numpy , pandas, matplotlib, scikit-learn for Creating ML algorithms and Data Visualization.
  • From this ML Course you will gain in-depth Practical Knowledge on Data Visualization & Data analysis for AI, ML and Data Science.
  • Our Machine Learning Courses help you to improve your big data analytics skills. Implement your Machine Learning Skills for Solving Complex Problems and build procedures for automation tasks.

Remote machine learning Training

  • Our, Machine learning online training – programme provides Online portal to study anytime, online classes to study flexibly , industry recognized certificate with, machine learning interview questions (and) machine learning interview questions training – for all the attendees. machine learning jobs in chennai – preferred students can learn online and can come down to office to learn and resolve your doubts directly from the trainers.
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Machine Learning Training in Chennai questions and answers

Is machine learning still in demand?

  • Over the past five years alone the number of AI-related job postings on job portals has increased by 100 percent, according to the platform’s latest AI talent report.

Who can apply for this Machine learning course ?

  • Students belonging to 1st year, 2nd year, 3rd year and 4th year Electronics, Instrumentation, Electronics and Telecommunications and Biomedical engineering can apply for this machine learning course.
  • Students from Computer science Engineering or Information Technology Engineering can also apply for this course.

Why should I learn this course from kaashiv infotech ?

  • Fully Practical/hands-on training
  • 50+ hours course duration
  • Industry professional faculties
  • Certification guidance
  • Own course materials
  • Interview preparation
  • Reasonable fees structure

Who is my trainer and how they are selected ?

  • Our trainers are more than 10+ years of experience in course relevant technologies.
  • Trainers are expert level in the subjects they explain because they continue to spend time working on real-world industry applications.
  • Trainers have skilled on real-time projects in their industries.
  • Are working professionals working in international companies such as CTS, TCS, HCL Technologies, etc…
  • Trained more than 1500+ students in a year.
  • Strong theoretical & practical knowledge.

What certification will I get after Machine Learning Training ?

  • Each student will be given industry-recognized course completion certificate.
    .

What would we gain after completion of this training program ?

  • A student will be able to get knowledge on the Machine Learning concepts. Along with technical features, soft skills would also be trained which will help an individual to crack the interviews.

Is career in Machine Learning a good choice ?

  • Surely yes. As per the market tendency, Machine Learning professionals are in huge demand. Based on the job roles they can select and complete their certification and hike to the higher levels.

Is there an online training which is available for this course ?

  • Yes. We provide online training programs as well. Timing is completely selected basis the availability of the candidate. Hence very flexible and comfortable.

How to get machine learning training ?

Machine Learning Interview Questions and Answers

What is Machine Learning ?

  • Machine learning is a subject of computer science which deals with system programming in order to study and improve with experience.  For ex: Robots are automatic so that they can perform the task based on data they gather from sensors. It automatically studies programs from data.

 

Datamining Vs Machine Learning ?

  • Machine learning tells the study, design and development of the algorithms that give computers the ability to learn without being clearly programmed.
  • While, data mining can be defined as the process in which the unstructured data tries to extract data or unknown interesting patterns.  In this process machine learning algorithms are used.

 

What are the stages to build the hypotheses or model in machine learning?

  • Model building
  • Model testing
  • Applying the model

 

What is ‘Overfitting’ in Machine learning?

  • In machine learning, when a statistical model defines random error instead of underlying relationship ‘overfitting’ occurs.  When a model is too complex, overfitting is normally observed, because of having too many parameters with respect to the number of training data types. The model displays poor performance which has been overfit.

 

Why overfitting happens ?

  • The overfitting exists as the conditions used for training the model is not the same as the principles used to judge the efficiency of a model.

 

What is inductive machine learning ?

  • The inductive machine learning includes the process of learning by examples, where a system, after a set of observed examples tries to make a general rule.

 

What are the five popular algorithms of Machine Learning ?

  • Neural Networks (back propagation)
  • Probabilistic networks
  • Decision Trees
  • Nearest Neighbor
  • Support vector machines

 

What are the different Algorithm techniques in Machine Learning?

  • Supervised Learning
  • Unsupervised Learning
  • Semi-supervised Learning
  • Reinforcement Learning
  • Transduction

 

what is the function of ‘Unsupervised Learning’ ?

  • Find groups of the data
  • Find low-dimensional symbols of the data
  • Find interesting directions in data
  • Interesting coordinates and correlations
  • Find novel observations/ database cleaning

 

what is the function of ‘Supervised Learning’?

  • Classifications
  • Speech recognition
  • Regression
  • Predict time series
  • Annotate strings

 

In what areas Pattern Recognition is used?

Pattern Recognition can be used in

  • Computer Vision
  • Speech Recognition
  • Data Mining
  • Statistics
  • Informal Retrieval
  • Bio-Informatics

 

What is Genetic Programming?

  • Genetic programming techniques used in machine learning. The model is based on the selecting and testing the best choice between a set of results.

 

What are the two methods used for the calibration in Supervised Learning?

The methods used for predicting good chances in Supervised Learning are

  • Platt Calibration
  • Isotonic Regression

These methods are considered for binary classification, and it is not trivial.

 

 

Which method is frequently used to prevent overfitting?

  •  ‘Isotonic Regression’ method is used to prevent an overfitting issue.

 

What are Bayesian Networks (BN) ?

  • Bayesian Network is used to represent the graphic model for possibility relationship between the set of variables.

 

What are the different methods for Sequential Supervised Learning ?

  • Sliding-window methods
  • Recurrent sliding windows
  • Hidden Markow models
  • Maximum entropy Markow models
  • Conditional random fields
  • Graph transformer networks

 

What are the different categories you can categorized the sequence learning process?

  • Sequence prediction
  • Sequence generation
  • Sequence recognition
  • Sequential decision

 

What is sequence learning?

  • Sequence learning is a method of teaching and learning in a logical manner.

 

What are two techniques of Machine Learning ?

The two techniques of Machine Learning are

  • Genetic Programming
  • Inductive Learning

 

What is clustering in Machine Learning ?

Clustering is a technique used in unsupervised learning that includes grouping data points. If you have a set of data points, you can use of the clustering algorithm. This technique will allow to classify all the data points into their specific groups. The data points that are thrown into the same category have similar features and properties, whereas the data points that fit to different groups have different features and properties. This method allows to perform statistical data analysis.

 

What are the differences between Supervised and Unsupervised Machine Learning ?

Supervised learning:

Supervised learning algorithm use labelled data to get trained. The models take direct feedback to confirm whether the output that is being projected is, indeed, correct. Also, both the input data and the output data are provided to the model, and the main goal is to train the model to predict the output when it accepts new data. It can mainly divide into two parts, classification and regression. It offers exact results.

Unsupervised learning:

Unsupervised learning algorithms use unlabelled data for training purposes. In this, the models do not take any feedback, and unlike the case of supervised learning, these models classify hidden data trends. The unsupervised learning model is only provided with the input data, and its main goal is to identify hidden patterns to extract information from the unknown sets of data. It can also be classified into two parts, i.e., clustering and associations.

 

 

Differentiate between classification and regression in Machine Learning.

  • Classification: 
    • In classification, we try to create a Machine Learning model that supports us in separating data into categories. The data is labelled and considered based on the input parameters.
    • For ex, see that we want to make predictions on the churning out customers for a specific product based on some data recorded. Either the customers will churn out or they will not. So, the labels for this would be ‘Yes’ and ‘No.’
  • Regression: 
    • It is the process of creating a model for distinguishing data into continuous real values, instead of using classes or discrete values. It can also classify the distribution movement depending on the old data. It is used for predicting the occurrence of an event based on the degree of association of variables.
    • For example, the prediction of weather condition depends on reasons such as temperature, air pressure, solar radiation, elevation of the area, and distance from sea. The relation between these factors supports us in predicting the weather condition.

 

How can you avoid overfitting ?

  • By using a lot of data overfitting can be avoided, overfitting happens relatively as you have a small dataset, and you try to learn from it. But if you have a small database and you are required to come with a model based on that. In such situation, you can use a technique known as cross validation.
  • In this method the dataset splits into two section, testing and training datasets, the testing dataset will only test the model while, in training dataset, the datapoints will come up with the model.
  • In this technique,  a model is usually given a dataset of a known data on which training (training data set) is run and a dataset of unknown data against which the model is tested. The idea of cross validation is to define a dataset to “test” the model in the training phase.

 

 What is ‘Training set’ and ‘Test set’?

  • In various areas of information science like machine learning, a set of data is used to discover the potentially predictive relationship known as ‘Training Set’. Training set is an examples given to the learner, while Test set is used to test the accuracy of the hypotheses generated by the learner, and it is the set of example held back from the learner. Training set are distinct from Test set.

 

What is algorithm independent machine learning ?

Machine learning in where mathematical foundations is independent of any particular classifier or learning algorithm is referred as algorithm independent machine learning.

 

What is Model Selection in Machine Learning ?

  • The process of selecting models among different mathematical models, which are used to describe the same data set is known as Model Selection. Model selection is applied to the fields of statistics, machine learning and data mining.

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