Machine Learning Training/Course by Experts

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Our Training Process

Machine Learning - Syllabus, Fees & Duration

Module 1 : CORE PYTHON

  • Short history
  • Introduction
  • Features of Python
  • Python2 Vs Python 3
  • Python Installation
  • Python Interpreter
  • How to Run Python
  • Basic Syntax
  • Python Identifiers, Keywords and Indentation Rules
  • Type Checking
  • Input, Output, Variables, Data Type and Datatype Casting

Module 2 : MACHINE LEARNING

  • Data Analysis
  • Data Visualization
  • Data Classification
    • Supervised Learning
    • Unsupervised Learning

Module 3 : SUPERVISED LEARNING

  • Classification
    • K-Nearest Neighbours
    • Decision Tree
    • Naive Bayes
    • Logistic Regression
    • Support Vector Machine
    • Random Forest
    • Logistic Regression
  • Regression
    • Single Linear Regression
    • Multiple Linear Regression

Module 4 : UNSUPERVISED LEARNING

  • Clustering
    • Hierarchical Clustering
    • KMeans Algorithm Association

Module 5 : DATA PREPROCESSING

  • PCA
  • Dimensionality reduction
  • Correlation
  • Features Extraction Algorithm

Download Syllabus - Machine Learning
Course Fees
10000+
20+
50+
25+

Machine Learning Jobs in Melbourne

Enjoy the demand

Find jobs related to Machine Learning in search engines (Google, Bing, Yahoo) and recruitment websites (monsterindia, placementindia, naukri, jobsNEAR.in, indeed.co.in, shine.com etc.) based in Melbourne, chennai and europe countries. You can find many jobs for freshers related to the job positions in Melbourne.

  • Machine Learning Engineer
  • Data Architect
  • Data Engineer
  • Artificial Intelligence Analyst
  • Data Mining Specialists
  • BigQuery Engineer
  • Machine Learning Specialist
  • Data Manager
  • Advanced Analytics Engineer
  • Data Scientist

Machine Learning Internship/Course Details

Machine Learning internship jobs in Melbourne
Machine Learning Anyone who completes this course can expect a typical salary increase of 48% and be hired by one of our 100+ hiring employers. An overview of artificial intelligence and machine learning, fundamental principles for machine learning, data pre-processing, feature extraction, regression, logistic regression, nave Bayes, decision trees, kernel methods, and support vector machine and k-means and hierarchical clustering are among the topics covered in this course. . Check out our NESTSOFT courses in Melbourne if you're interested in learning more about Machine Learning. The student will be able to create and apply pattern classification algorithms to categorize multivariate data, create and apply regression algorithms to uncover correlations between data variables, and use reinforcement learning methods to operate complicated systems after finishing the course. You'll need data training capabilities, algorithm basics, advanced, automation, and iterative processes, ensemble modeling, and scalability to build a strong ML (machine learning) system. Candidates will acquire the fundamental concepts and intuition underpinning modern machine learning algorithms, as well as a more formal knowledge of how, when, and why they work, in this course. We live in a world surrounded by humans who can study everything using their abilities and learning abilities, as well as machines that follow our directions. You'll also have the opportunity to work as a data scientist, Machine Learning engineer, or data engineer for several years and learn from industry specialists. Machine learning is the study of computational algorithms that can automatically improve witpracticese and is implemented as part of artificial intelligence.

List of All Courses & Internship by TechnoMaster

Success Stories

The enviable salary packages and track record of our previous students are the proof of our excellence. Please go through our students' reviews about our training methods and faculty and compare it to the recorded video classes that most of the other institutes offer. See for yourself how TechnoMaster is truly unique.

List of Training Institutes / Companies in Melbourne

  • Buildxact | Location details: level 1/411 Collins St, Melbourne VIC 3000, Australia | Classification: Software company, Software company | Visit Online: buildxact.com.au | Contact Number (Helpline): +61 1800 965 597
  • AustralianIndustrialSystemsInstitute | Location details: 1/398 Lonsdale St, Melbourne VIC 3000, Australia | Classification: Vocational school, Vocational school | Visit Online: aisi.edu.au | Contact Number (Helpline): +61 3 9670 0915
  • Buildxact | Location details: level 1/411 Collins St, Melbourne VIC 3000, Australia | Classification: Software company, Software company | Visit Online: buildxact.com.au | Contact Number (Helpline): +61 1800 965 597
  • LonsdaleInstituteMelbourne | Location details: Level 4/30 Church Ln, Melbourne VIC 3000, Australia | Classification: Educational institution, Educational institution | Visit Online: lonsdaleinstitute.edu.au | Contact Number (Helpline): +61 3 9639 0543
  • AcademiaInstitute | Location details: 399 Lonsdale St, Melbourne VIC 3000, Australia | Classification: Educational institution, Educational institution | Visit Online: academia21.com | Contact Number (Helpline): +61 3 9671 4755
  • MonarchInstitute | Location details: Lvl 22/535 Bourke St, Melbourne VIC 3000, Australia | Classification: Educational institution, Educational institution | Visit Online: monarch.edu.au | Contact Number (Helpline): +61 1300 738 955
  • Buildxact | Location details: level 1/411 Collins St, Melbourne VIC 3000, Australia | Classification: Software company, Software company | Visit Online: buildxact.com.au | Contact Number (Helpline): +61 1800 965 597
  • Nexacu | Location details: level 3/466 Little Lonsdale St, Melbourne VIC 3000, Australia | Classification: Software training institute, Software training institute | Visit Online: nexacu.com.au | Contact Number (Helpline): +61 1300 886 190
  • Elabor8 | Location details: Spaces, Two Melbourne Quarter, 697 Collins St, Docklands VIC 3008, Australia | Classification: Business management consultant, Business management consultant | Visit Online: elabor8.com.au | Contact Number (Helpline): +61 1300 352 278
  • PlatinumProfessionalTraining | Location details: 605/343 Little Collins St, Melbourne VIC 3000, Australia | Classification: Training centre, Training centre | Visit Online: platinumaccg.com.au | Contact Number (Helpline): +61 3 9642 0393
  • IndustryConnect | Location details: 385 Bourke St, Melbourne VIC 3000, Australia | Classification: Software training institute, Software training institute | Visit Online: industryconnect.org | Contact Number (Helpline): +61 1300 508 817
  • Prog360Melbourne,Australia-MachineLearning,IOT,DeepLearning,PythonCorporateTraining | Location details: | Classification: Software company, Software company | Visit Online: prog360.com | Contact Number (Helpline): +61 3 9013 6917
  • OrderMate | Location details: 59 Fennell St, Port Melbourne VIC 3207, Australia | Classification: Software company, Software company | Visit Online: ordermate.com.au | Contact Number (Helpline): +61 1300 667 067
  • SyntheticDataPtyLtd | Location details: 530 Little Collins St, Melbourne VIC 3008, Australia | Classification: Software training institute, Software training institute | Visit Online: | Contact Number (Helpline): +61 419 891 932
  • ServiceNow | Location details: Level 16/17, 477 Collins St, Melbourne VIC 3000, Australia | Classification: Software company, Software company | Visit Online: servicenow.com | Contact Number (Helpline): +61 3 8626 8600
  • ProjectTMA | Location details: L8/350 Collins St, Melbourne VIC 3000, Australia | Classification: Learning center, Learning center | Visit Online: projecttma.com.au | Contact Number (Helpline): +61 1300 363 822
 courses in Melbourne
It is a safe and vibrant global city renowned for its livability, great beaches, friendly people, iconic highways, cultural experiences, a diverse food and wine scene and a dynamic student population. edu. au Victoria University Polytechnic victoriapolytechnic. edu. com/schools/melbourne-english-schools. edu. With so many top universities to choose from, can take time. Academic year University classes usually start in March or July and end in early December. edu. This city offers a quality student experience - world-class learning opportunities - and attracts research-rich development centers of the world's best scientists.

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