Machine Learning Tutorials

Welcome to LabEx! In this first lab, you'll dive into Python basics, covering essentials like the Python interpreter, variables, assignment, input/output operations, and exiting the interpreter.

Explore the fundamentals of Python Core, from data types and control flow to object-oriented programming and standard library usage. Become a proficient Python developer with this comprehensive tutorial.

Explore the power of the Win32 API in Python to automate Windows tasks, customize user interfaces, and integrate your applications seamlessly with the Windows ecosystem.

Explore the power of Python's standard library and learn how to leverage its core package for efficient and robust programming. Discover essential modules for file management, data structures, numerical computations, and more.

In this project, you will learn how to calculate the damage values of two high-performance laser weapons developed by the Galactic Empire's weapon research institute. The weapon equipment lab is responsible for testing the weapon values, and you will help them by implementing the damage calculation process.

In this project, you will learn how to perform one-hot encoding on label data for a single-label classification task. One-hot encoding is a common technique used to transform categorical variables into a format that can be used by machine learning algorithms.

In this lab, you will learn how to use Python's unittest module to write and run test cases.

In computer science, a queue is a data structure that follows the First-In-First-Out (FIFO) principle. It is an ordered list of elements where an element is inserted at one end and removed from the other end. A stack, on the other hand, follows the Last-In-First-Out (LIFO) principle. It is an ordered list of elements where an element is inserted and removed from the same end. In this challenge, we will implement a queue using two stacks.

In computer science, a stack is an abstract data type that serves as a collection of elements, with two main operations: push, which adds an element to the collection, and pop, which removes the most recently added element that was not yet removed. In some cases, we may need to implement a set of stacks, where each stack has a limited capacity. When a stack reaches its capacity, a new stack is created to store additional elements. In this challenge, we will implement a SetOfStacks class that wraps a list of stacks, where each stack is bound by a capacity.

In computer science, the Longest Increasing Subsequence (LIS) problem is to find the length of the longest subsequence of a given sequence such that all elements of the subsequence are sorted in increasing order. This subsequence is not necessarily contiguous, or unique.

Sorting is a fundamental operation in computer science. It is the process of arranging data in a specific order. Selection sort is one of the simplest sorting algorithms. It works by repeatedly finding the minimum element from the unsorted part of the list and putting it at the beginning. This process is repeated until the entire list is sorted.

An anagram is a word or phrase formed by rearranging the letters of a different word or phrase. For example, 'listen' and 'silent' are anagrams of each other. In this challenge, we will be sorting an array of strings so that all anagrams are next to each other.

In computer science, the longest common subsequence (LCS) problem is to find the longest subsequence common to all sequences in a set of sequences (often just two sequences). It differs from problems of finding common substrings: unlike substrings, subsequences are not required to occupy consecutive positions within the original sequences.

In this lab, you will learn how to convert hexadecimal color codes to their corresponding RGB (red, green, blue) values using a Python function that leverages list comprehension and type conversion.

A binary search tree (BST) is a tree data structure in which each node has at most two children, which are referred to as the left child and the right child. A valid BST is a tree in which all the nodes in the left subtree of a node have a value less than the node's value, and all the nodes in the right subtree have a value greater than the node's value. In this challenge, we will determine if a given tree is a valid binary search tree.

A min heap is a binary tree data structure that satisfies the heap property, where the parent node is always less than or equal to its children. In a min heap, the root node is always the minimum value in the tree.

Inverting a binary tree means swapping all left and right node pairs. This is a common problem in computer science and is often used as an interview question.

The Two Sum problem is a classic algorithmic problem in computer science. It requires finding two indices in an array that sum up to a specific value. This problem has a wide range of applications, including in data science, machine learning, and finance.