Statistics, Machine Learning, R for College and Grad School hide this posting unhide

QR Code Link to This Post Tutoring for college and graduate school statistics. You will learn the theoretical aspect of statistics, as well as applied statistics, and how to build statistical models. Some topics include: empirical risk minimization, high-dimensional inference, and optimization.
Theory Courses: Probability Theory, Statistical Inference, Linear Regression, Data Mining, Bayesian Statistics, High-Dimensional Statistics, and other Ph.D. courses.
Statistical Modeling: Bayesian Inference, Monte Carlo, Gaussian Processes, Probabilistic Models, Parametric and nonparametric estimation, etc.
Machine Learning: Ridge Regression, LASSO, k-means, EM, Belief Propagation, Variational Inference, Neural Network, Statistical Learning Theory
Statistical computing: R programming, Matlab, STATA, Python, Java, C For example,
    1. Linear regression: y = β₀+ β₁X₁ + β₂ X₂ + ε
        β = argmin{Σ(y-β₀-β₁X₁- β₂ X₂)²}

    2. Posterior inference on θ: P(θ|x, y) ∝ P(x, y|θ)P(θ)

    3. Convex optimization
        minimize cᵀx
        subject to aᵢᵀx ≤ bᵢ, for i = 1,...n

    4. Information theory: H(P(x)) = - E[log(P(x))] = - ∫ P(x) logP(x) dx

Rate: $60/hr

Location: Central Jersey (West Windsor, Lawrenceville, Somerset, Montgomery) or a location near you

You can contact by text or email. or walkingon2008 AT aol DOT com




Location: New Jersey -
Added on 12 days ago and expires on 23 May, Ad id: 754872          85 visits