MY-ASSIGNMENTEXPERT™可以为您提供sydney COMP5318 Machine Learning机器学习课程的代写代考和辅导服务！
这是悉尼大学机器学习课程的代写成功案例。
COMP5318课程简介
Machine learning is the process of automatically building mathematical models that explain and generalise datasets. It integrates elements of statistics and algorithm development into the same discipline. Data mining is a discipline within knowledge discovery that seeks to facilitate the exploration and analysis of large quantities for data, by automatic and semiautomatic means. This subject provides a practical and technical introduction to machine learning and data mining. Topics to be covered include problems of discovering patterns in the data, classification, regression, feature extraction and data visualisation. Also covered are analysis, comparison and usage of various types of machine learning techniques and statistical techniques.
Prerequisites
At the completion of this unit, you should be able to:
- LO1. understand the basic principles, strengths, weaknesses and applicability of machine learning algorithms for solving classification, regression, clustering and reinforcement learning tasks.
- LO2. have obtained practical experience in designing, implementing and evaluating machine learning algorithms
- LO3. have gained practical experience in using machine learning software and libraries
- LO4. present and interpret data and information in verbal and written form
COMP5318 Machine Learning HELP（EXAM HELP， ONLINE TUTOR）
(foundations: distance)
Consider two parallel hyperplanes in $R^d$ :
$$
\begin{aligned}
& H_1: \mathbf{w}^T \mathbf{x}=+3 \
& H_2: \mathbf{w}^T \mathbf{x}=-2
\end{aligned}
$$
where w is the normal vector. What is the distance between $H_1$ and $H_2$ ?
(foundations: differential and partial differential)
Let $f(x)=\ln \left(1+e^{-2 x}\right)$. What is $\frac{d f(x)}{d x}$ ? Let $g(x, y)=e^x+e^{2 y}+e^{3 x y^2}$. What is $\frac{\partial g(x, y)}{\partial y}$ ?
(foundations: chain rule)
Let $f(x, y)=x y, x(u, v)=\cos (u+v), y(u, v)=\sin (u-v)$. What is $\frac{\partial f}{\partial v}$ ?
(foundations: integral)
What is $\int_5^{10} \frac{2}{x-3} d x$ ?
(foundations: gradient and Hessian)
Let $E(u, v)=\left(u e^v-2 v e^{-u}\right)^2$. Calculate the gradient
$$
\nabla E(u, v)=\left(\begin{array}{l}
\frac{\partial E}{\partial u} \
\frac{\partial E}{\partial v}
\end{array}\right)
$$
and the Hessian
$$
H(u, v)=\left(\begin{array}{ll}
\frac{\partial^2 E}{\partial u \partial u} & \frac{\partial^2 E}{\partial u \partial v} \
\frac{\partial^2 E}{\partial v \partial u} & \frac{\partial^2 E}{\partial v \partial v}
\end{array}\right)
$$
at $u=1$ and $v=1$.
(foundations: Taylor’s expansion)
Let $E(u, v)=\left(u e^v-2 v e^{-u}\right)^2$. Write down the second-order Taylor’s expansion of $E$ around $u=1$ and $v=1$.
MY-ASSIGNMENTEXPERT™可以为您提供SYDNEY COMP5318 MACHINE LEARNING机器学习课程的代写代考和辅导服务！
