Best Machine learning Course In Bangalore with Placement

1900

Machine Learning course in Bangalore KaLYAN NAGAR

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100 hrs

Duration

1.30hr

Per Day

Machine Learning course Training in Bangalore

Cambridge InfoTech offers Machine learning course training in Bangalore Kammanahalli from our mentors. Learn a deep python machine learning course in Tumkur. Our educator area unit operating in and connected technologies for a lot of years in MNC’s. we have bent to respond to trade desires which we have a tendency to area unit giving Machine Learning coaching in Bangalore throughout many sensible approaches. Our team of Machine Learning trainers offers deep classroom coaching, Machine learning online coaching, and Machine Learning company coaching services. we have a bent to framed our data to match with the important world wants for every beginner level to a sophisticated level. Our coaching is handled in either weekday or weekend programs depends on the participant’s demand.

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Machine Learning Training in BangaloreMachine Learning course Training in Bangalore

Best Machine Learning course Training in Bangalore

We do provide Fast-Track coaching in Bangalore and matched deep Machine Learning coaching in Bangalore. Here area unit the most vital topics we’ve got an inclination to cowl beneath this Introduction to R, processing exploitation R, Programming in R, Graphics exploitation R, python Machine Learning, deep learning, Training and testing in machine learning. every topic is coated throughout a top approach with examples.

Why Machine Learning course Training in Cambridge InfoTech?

Cambridge Infotech placed in varied places in Bangalore. we’ve got an inclination to area units simplest coaching Institute offers certification familiarized python Machine Learning course training in Bangalore. Our participants are eligible to clear every kind of interview at the highest of our sessions. we’ve got an inclination to unit building a team of Machine Learning trainers and participants for his or her future facilitate and facilitate among the topic. Our coaching is focused on serving in placements equally.

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We have a separate unit of time team professionals World Health Organization pays attention to all or any of your interview needs. Our python coaching in Bangalore Course Fees is extraordinarily moderate compared to others

Machine Learning course Training in Bangalore

The core of our learning center is our students. We look for the latest case study which builds correct knowledge. Cambridge including Cambridge’s team always working on how to deliver the latest knowledge.

  • Get trained with the right place which knows the value of your time and money.
  • Get trained in the right hand which helps bridge the gap between you and the company.
  • Come join our team who knows how every individual has a hidden learning pattern. Our core values – students first, the knowledge we build in the classroom.
  • Our students are everything and our teamwork relentlessly to train and make the best fit in the presence requirement.

You have completed or pursuing Under Graduate, Post Graduate BE or B Tech and wanted to look your carrier in Data Science, Cambridge is ready to help you.
Learn Data Analysis, Data Science, Machine Learning or Artificial Intelligence, ANN, CNN, RNN. 

Syllabus of Machine Learning course training in Bangalore

  • Data Analyst in R 
  • Fundamental of R
  • R syntax
  • Analysis of Data
  • Cleaning  Data                     
  • Data visualization
  • Packages learn –
  • Tidy-verse
  • SQL Query for
  • Basic Statistics:
  • Data Aggregation Technique
  • Combine Data Sets
  • Transform and Reshape data
  • Clean data and handle missing data

This path will make you how to work efficiently as a Data Analysis using R.
We have designed a course in such a way there is no Prerequisite and no prior experience required.
Our learning path is defined as LEARN WITH EXAMPLE. We will learn with CASE STUDY.

  • Basic and Intermediate R Programming concepts.
  • R Packages as Tidy-verse and others.
  • How to use multiple charts like BAR, PIE, 
  • Probability, Quartile, Mean, 
  • How to clean data
  • handle missing data
  • create data for analysis.
  • You have completed or pursuing Under Graduate, Post Graduate, BE or B Tech and wanted to look your carrier in Data Science, Cambridge is ready to help you.
    We need to have prior knowledge as prerequisites for the Machine Learning path. Linear Algebra basics – Matrices, Vectors, Statistics basics.
    When Data is abundant with 100 or more than 100 variables than we use machine learning.
  •  Supervised and Unsupervised Learning
  •  Linear and Logistic Regression
  •  Decision Trees
  •  Random Forest
  •  Kernel SVM
  •  K-Means Cluster
  •  Naïve Bayes
  •  NLP (Natural Language Processing)
  •  Boosting and Bagging Techniques
  •  Neural Network 
  •  Deep Neural Network fundamental.
  •  Total Course Duration: 60 hours.
  •  Machine Learning with Python / R
  •  We have designed a course in such a way there is no Prerequisite and no prior experience required.
  •  Our learning path is defined as LEARN WITH EXAMPLE. We will learn with CASE STUDY.
  • Machine Learning Course Overview.
  • Python Environment setup and Essentials.
  • Mathematical computing with Python(Numpy).
  • Scientific computing with python(Scipy).
  • Data Manipulation with Python (Pandas).
  • Machine Learning with Scikit-learn.
  • Data Visualization in Python using (Matplotlib).
  • R Environment setup and essentials 
  • R for data science
  • How to import data in R
  • Basics of RStudio
  • concepts – data frames, matrices, vectors, list 
  • comparison operator to make the calculation
  • working with string 
  • Data Visualization in R 
  • Supervised and Unsupervised Learning
  • Linear and Logistic Regression
  • Decision Trees
  • Random Forest
  • Kernel SVM
  • K-Means Cluster
  • Naïve Bayes
  • Text Analytics (NLP)
  • Boosting and Bagging Techniques
  • Neural Network 
  • Deep Network fundamentals.
  • Sample and Population data
  • The fundamental of descriptive Statistics 
  • The measure of Central Limit theory
  • Distributions
  • Hypothesis testing
  • The assumption for linear regression analysis
  • Linearity
  • Normality and Homoscedastic
  • Autocorrelation
  • Multicollinearity
  • How to prepare a CV and ready for Interview.

Total Duration: 100 hours (3 months).

Online Mentorship is on demand.

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