Name               : Sandya

Experience        : 18+ Years of Industry

Trainee Details   :

** An ardent academician, trainer and consultant with proven proficiency in the fields of IT focusing on AI/Machine Learning, Data Science, Business Analytics and Cyber Security.
** Overseas experience in university-level post-graduate teaching and guidance.
** Working with pure play analytics vendors as AI/ Machine Learning, Data Science and Cyber Security Trainer and Consultant.
** Carried out a number of IT projects based on Machine Learning, Data Science, Cyber Security and Cloud Computing.

Course Timings  :

Course Duration :

work work work work

What you learn in Machine Learning Course?

  • Statistics and Probability

    • Descriptive Statistics
    Intoduction to Statistics
    Charts and Graphs
    Descriptive Statistics
    Probability
    Distributions and Sampling
    Discrete Distributions
    Continuous Distribution
    Sampling Distribution
    Bayes Theorem
    Making Inferences about Population Parameters
    Non-Parametric Statistics

  • Machine Learning

    • Linear Regression
    Covariance Corelation
    Simple Linear Regression
    Multiple Linear Regression
    Logistic Regression
    Logistic Function
    Confusion Matrix
    Naive Bayes Classifier
    Future Engineering and Regularization
    PCA
    EDA-Preprocessing
    Lasso
    Ridge Regression
    Over Fitting
    Clustering
    Distance Caluculation Hierarchical Clustering
    K Medoids Clustering
    Recommendation Systems
    Decision Tree
    Ensemble Methods
    KNN Algorithm
    Support Vector Machines

  • Python programming

    • Introduction to Python
    Basic operations
    Values,Types and Variables
    Conditional Statements
    Loops
    Command Line Arguments
    Python Packages for Data Science
    Pandas
    Numpy
    Scipy
    Matplotlib
    Seaborn
    SKlearn

  • Deep Learning

    • Artificial Neural Networks
    Auto Encoders
    Optimization Techniques
    Linear Programming
    Monte Carlo Simulation
    Genetic Algorithms
    Gradient Descent
    Markov chains

  • Computer Vision

    • Convolution Neural Networks
    Image Augmentation
    Image Classification
    Image Segmentation
    Introduction to RRN
    Limitations of RRN
    Improvement of RNN
    LSTM

  • Natural Language Processing

    • Text Processing
    Text Indexing
    Crawling
    Tokenization
    Lemmatization
    Part-of-Speech
    Tagging
    Relevance Ranking
    TF and IDF
    Vector Space Model
    Evaluation Metrics for Ranking Link
    Spam Detection Algorithms
    Sentiment Analysis

  • Artificial Intelligence

    • ChatBot
    Anotomy of ChatBot
    A Simple rule base ChatBot using Slack
    Understanding Google's Dialogflow
    Bringing the ChatBot to Life

Pay for Course

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