Machine Learning Course

Machine Language Content

    Introduction to Artificial Intelligence and Machine Learning

    The name machine learning was created in 1959 by Arthur Samuel. Tom M. Mitchell provided a widely quoted, more formal definition of the algorithms studied within the machine learning field: "A computer program is alleged to find out from experience E with reference to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E." his definition of the tasks during which machine learning cares offers a fundamentally operational definition instead of defining the sector in cognitive terms.

    Machine learning (ML) is that the scientific study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, relying on patterns and inference instead. It’s seen as a subset of AI. Machine learning algorithms build a mathematical model supported sample data, mentioned as "training data", so on form predictions or decisions without being explicitly programmed to perform the task. Machine learning algorithms are utilized during a good kind of applications, like email filtering and computer vision, where it's difficult or infeasible to develop a typical algorithm for effectively performing the task.

    Machine learning is closely associated with computational statistics, which focuses on making predictions using computers. The study of mathematical optimization delivers methods, theory and application domains to the sector of machine learning. Data processing may be a field of study within machine learning, and focuses on exploratory data analysis through unsupervised learning. In its application across business problems, machine learning is additionally mentioned as predictive analytics.

    Best Machine Learning Course

    Learn Best Machine Learning Certification courses from AppTechnoServices. This course is designed to help Machine Learning & AI professionals boost their careers. This course provides a broad introduction to machine learning, data mining, and statistical pattern recognition. This course provides a concise introduction to the fundamental concepts in machine learning and popular machine learning algorithms. One of the best things about this course we give you complete practical knowledge of every algorithm of machine learning. Google machine learning is best part of this course. If you looking best Machine learning instituted and training center in Delhi NCR, AppTechnoServices is right choice for machine learning course.

  •  Artificial Intelligence
  •  Machine Learning
  •  Machine Learning algorithms
  •  Applications of Machine Learning
  • Techniques of Machine Learning
  •  Supervised learning
  •  Unsupervised learning
  •  Semi-supervised and Reinforcement learning
  •  Bias and variance trade-off
  •  Representation learning
  • Data Preprocessing
  •  Data preparation
  •  Feature engineering
  •  Feature scaling
  •  Datasets
  •  Dimensionality reduction
  • Math Refresher
  •  Concepts of linear algebra
  •  Eigenvalues, eigenvectors, and eigendecomposition
  •  Introduction to Calculus
  •  Probability and statistics
  • Regression
  •  Regression and its types
  •  Linear regression: Equations and algorithms
  • Classification
  •  Meaning and types of classification
  •  Logistic regression
  •  K-nearest neighbors
  •  Support vector machines
  •  Kernel support vector machines
  •  Naive Bayes
  •  Decision tree classifier
  •  Random forest classifier
  • Unsupervised learning: Clustering
  •  Clustering algorithms
  •  K-means clustering
  • Introduction to Deep Learning
  •  Meaning and importance of Deep Learning
  •  Artificial Neural Networks
  •  TensorFlow