ARTIFICIAL INTELLIGENCE TRAINING IN DEHRADUN

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ABOUT ARTIFICIAL INTELLIGENCE TRAINING

A machine with the ability to perform cognitive functions such as perceiving, learning, reasoning and solve problems are deemed to hold an artificial intelligence. Artificial intelligence exists when a machine has cognitive ability. The benchmark for AI is the human level concerning reasoning, speech, and vision. In computer science, artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and animals. Leading AI textbooks define the field as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. SLOG Solutions pvt.ltd provides best summer/winter/regular training in dehradun for , artificial intelligence (AI).

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Artificial Intelligence(AI) is the simulation of human intelligence by machines. In other words, it is the method by which machines demonstrate certain aspects of human intelligence like learning, reasoning and self- correction. Since its inception, AI has demonstrated unprecedented growth. Sophia the AI Robot, is the quintessential example of this. The future of Artificial intelligence is hazy. But going by the bounds of progress AI has been making, it is clear AI will permeate every sphere of our life. Listed below are the diverse ways in which AI can change in the future.

ARTIFICIAL INTELLIGENCE TRAINING IN DEHRADUN


    NUMPY, PANDAS, STATISTICS & Mathematical

    •    Numerical Python (Numpy)
    •    Data Manipulation with Pandas
    •    Data Visualization
    •    Introduction to Statistics
    •    Types of Distributions
    •    Hypothesis Testing
    •    Bayesian Statistics
    •    Mathematical
    •    Statistics intuition

    MACHINE LEARNING

    •    Introduction to Machine Learning
    •    Supervised (Regression/ Classification)
    •    Unsupervised Learning
    •    EDA and DataWrangling
    •    Feature Selection and Dimensional Reduction
    •    Modelling Tools
    •    Cross-Validation and HyperParameter Tuning
    •    Evaluation Metrics and Improvement Techniques
    •    Criteria to Select Models
    •    Linear Regression
    •    Polynomial Regression
    •    Regularization with Lasso/Ridge Regression
    •    Step Regression
    •    Logistic Regression
    •    K Nearest Neighbours

    •    Support Vector Machine (SVM)
    •    Decision Tree
    •    Naive Bayes
    •    Ensembling
    •    Random Forest
    •    Time Series
    •    Unsupervised Learning
    •    K Means
    •    Dimensionality Reduction using PCA
    •    Hierarchical Clustering

    DEEP LEARNING

    •    Artificial Neural Networks In Python
    •    Activation Functions
    •    New Strategies for Optimizing
    •    Tensorflow
    •    Keras
    •    Pytorch
    •    OpenCV
    •    Types of Networks
    •    CNN(Convolutional Neural Network)
    •    Architectures
    •    Recurrent Neural Networks
    •    Transfer Learning
    •    AutoEncoders
    •    GANs
    •    NLP Natural Learning Process
    •    NLTK
    •    Attention Mechanism
    •    Miscellaneous

    REINFORCEMENT LEARNING AND ARTIFICIAL SUPER INTELLIGENCE

    •    Element of Reinforcement Learning
    •    OpenAI/Gym
    •    Dynamic Programming
    •    Markov Decision Process
    •    Monte Carlo Methods
    •    Temporal Difference

StartingEvery Tuesday

  • AI TRAINING IN DEHRADUN

  • 4 Months

  • 10 students

  • 1 Day

  • CALL 7456000240

  • Dual Certificate

32000

StartingEvery Tuesday

  • AI TRAINING IN DEHRADUN

  • 4 Months

  • 10 students

  • 1 Day

  • CALL 7456000240

  • Dual Certificate

32000