Machine Learning Training 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 San Francisco

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 San Francisco, chennai and europe countries. You can find many jobs for freshers related to the job positions in San Francisco.

  • 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 San Francisco
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. 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. As a result of the increased demand, experts have been able to land the highest-paying positions. Machine learning is the study of computational algorithms that can automatically improve witpracticese and is implemented as part of artificial intelligence. Can a machine, like a human, learn from skills or previous data? So here's where Machine Learning comes in. 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. Anyone who completes this course can expect a typical salary increase of 48% and be hired by one of our 100+ hiring employers. 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. By enrolling in NESTSOFT machine learning classes, you will gain exposure to industrial projects or machine learning certification from a specific area. Check out our NESTSOFT courses in San Francisco if you're interested in learning more about Machine Learning.

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 San Francisco

  • HackReactor | Location details: 44 Tehama St, San Francisco, CA 94105, United States | Classification: Computer training school, Computer training school | Visit Online: hackreactor.com | Contact Number (Helpline): +1 415-268-0355
  • EFInternationalLanguageCampus-EnglishCoursesInSanFrancisco | Location details: 1355 Sansome St #4, San Francisco, CA 94111, United States | Classification: English language school, English language school | Visit Online: ef.com | Contact Number (Helpline): +1 415-409-0800
  • AIRTELEXPRESS(AKSHAYTELECOM-AuthorizedChannelPartnerOfBhartiAirtel) | Location details: Shop No- 3, San francisco Building, Tokarkhada, Silvassa, Dadra and Nagar Haveli 396230, India | Classification: Telecommunications service provider, Telecommunications service provider | Visit Online: | Contact Number (Helpline): +91 96010 49362
Ackerman right now confronted a unstable difficulty concerning a chain of desegregation fits and countersuits that had all started in 1983 with San Francisco NAACP v. Knowing that Ackerman had applied a gadget at San Francisco Unified School District (SFUSD) that done each of these objectives, Riordan had requested her to quick his team of workers on what SFUSD had found out via 3 years of implementation. These corporations ranged from 12 to 25 individuals, relying on the scale of the faculty, and kingdom regulation and district coverage mandated their composition and responsibilities. With over 30 years of revel in in public training as a instructor, main and deputy superintendent in severa districts, Ackerman had maximum recently been the superintendent of the general public faculty gadget in Washington, D. , the entire quantity of college students scoring withinside the backside quartiles in studying and math on the SAT-9, a country wide norm-referenced test, become taken into consideration too excessive via way of means of district stakeholders. The board become accountable for setting up instructional desires and standards, approving curriculum, and approving the general price range and expenditures. The numerous scholar frame become 31% Chinese, 21% Latino, 15% AfricanAmerican, 10% White, 7% Filipino, and 16% different non-white minorities. As a result, the district operated below a consent decree, controlled via way of means of a federal judge, which required SFUSD to satisfy instructional fairness goals for all college students withinside the district. The kingdom become thinking about mandating that faculty districts enforce a weighted scholar formula (WSF) to allocate monetary sources to person faculties, and circulate choice-making approximately the ones sources from primary workplaces to faculties. .

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