Geeky Codes | AI Engineering, Data Engineering & Machine Learning Tutorials
Geeky Codes 
Introduction: The task at hand is to implement a Python function that finds the kth lexicographically smallest integer in the range from 1 to n. To achieve this, we will use a depth-first search (DFS) approach, exploring the numbers in lexicographical order. Let’s dive into the implementation. Also checkout: Implementation: Explanation: Example: For n = … Read more
SELECT TOP number|percent column_name(s) FROM table_name SQL SELECT TOP Equivalent in MySQL and Oracle: MySQL Syntax: SELECT column_name(s) FROM table_name LIMIT number Example: SELECT * FROM Persons LIMIT 5 Oracle Syntax SELECT column_name(s) FROM table_name WHERE ROWNUM <= number Example SELECT * FROM Persons WHERE ROWNUM <=5 SQL TOP Example The “Persons” table: Now we … Read more
DELETE FROM table_name WHERE some_column=some_value Note: Notice the WHERE clause in the DELETE syntax. The WHERE clause specifies which record or records that should be deleted. If you omit the WHERE clause, all records will be deleted! SQL DELETE Example The “Persons” table: Now we want to delete the person “Tjessem, Jakob” in the “Persons” … Read more
SELECT column_name(s) FROM table_name ORDER BY column_name(s) ASC|DESC ORDER BY Example The “Persons” table: Now we want to select all the persons from the table above, however, we want to sort the persons by their last name.We use the following SELECT statement: The result-set will look like this: ORDER BY DESC Example Now we want … Read more
The “Persons” table: Now we want to select only the persons living in the city “Sandnes” from the table above. We use the following SELECT statement using Where clause: The result-set will look like this: Quotes Around Text Fields in SQL WHERE CLAUSE SQL uses single quotes around text values (most database systems will also … Read more
SQL is a standard language for accessing databases. How to use SQL to access and manipulate data in: MySQL, SQL Server, Access, Oracle, Sybase, DB2, and other database systems. SQL Syntax: SELECT Company, Country FROM Customers WHERE Country <> ‘USA’ SQL Result: SQL is a “standard language for accessing and manipulating databases”. What Can SQL … Read more
This content discusses dimensionality reduction approaches, focusing on projection and Manifold Learning. It explains how projection simplifies high-dimensional data, exemplified by datasets like the Swiss roll. Principal Component Analysis (PCA) is highlighted as a key algorithm for preserving variance while reducing dimensions, with SVD as a method for determining principal components.
Charlie possesses an extraordinary tool in his possession: a magic mirror capable of displaying right-rotated versions of any given word. This mirror offers a unique perspective, revealing fascinating transformations of words. In this blog post, we’ll delve into the Java code that produces these right-rotations, exploring how Charlie’s mirror brings about these linguistic metamorphoses. Also … Read more
Introduction Storing data in local computer memory represents the fastest and most reliable means to access it. The data could reside anywhere. However, you don’t actually interact with the data in its storage location. You load the data into memory from the storage location and then interact with it in memory. Uploading small amounts of … Read more
The Utopian Tree goes through 2 cycles of growth every year. Each spring, it doubles in height. Each summer, its height increases by 1 meter. A Utopian Tree sapling with a height of 1 meter is planted at the onset of spring. How tall will the tree be after growth cycles? For example, if the number of growth cycles is n=5, the calculations are as … Read more
A. Introduction to neural networksB. ANN architectures C. Learning methods D. Learning rule on supervised learning E. Feedforward neural network with Gradient descent optimization Introduction to neural networks Definition: the ability to learn, memorize and still generalize, prompted research in algorithmic modeling of biological neural systems. Human brain has the ability to perform tasks such … Read more
Introduction One way to get a diverse set of classifiers is to use very different training algorithms, as just discussed. Another approach is to use the same training algorithm for every predictor, but to train them on different random subsets of the training set. When sampling is performed with replacement, this method is called bagging … Read more
Introduction: Welcome to our comprehensive tutorial on Ensemble Learning! In this guide, we’ll delve into the fascinating world of Ensemble methods, exploring how they harness the collective intelligence of multiple models to achieve superior performance in machine learning tasks. Whether you’re a seasoned practitioner or just stepping into the realm of machine learning, understanding Ensemble … Read more
Decision Trees are also capable of performing regression tasks. Let’s build a regression tree using Scikit-Learn’s DecisionTreeRegressor class, training it on a noisy quadratic dataset with max_depth=2: from sklearn.tree import DecisionTreeRegressor tree_reg = DecisionTreeRegressor(max_depth=2) tree_reg.fit(X, y) The resulting tree is represented below This tree looks very similar to the classification tree you built earlier. The … Read more
In Previous blog we talked about Non Linear SVM Classifications. In this blog we will talk about Polynomial Kernel. Introduction Adding polynomial features is simple to implement and can work great with all sorts of Machine Learning algorithms (not just SVMs), but at a low polynomial degree it cannot deal with very complex datasets, and … Read more
In this series we bring new Data Scientist Interview Questions. You can read other tutorials related to same topic on our website. What is Cross Validation? Cross-Validation in Machine Learning is a statistical resampling technique that uses different parts of the dataset to train and test a machine learning algorithm on different iterations. The aim … Read more
In previous blog, We read about Soft margin Classification. In this blog we will talk about Non Linear SVM Classification. Introduction Although linear SVM classifiers are efficient and work surprisingly well in many cases, many datasets are not even close to being linearly separable. One approach to handling nonlinear datasets is to add more features, … Read more
In the dynamic world of business, where data-driven decisions reign supreme, the accuracy and reliability of classification models play a pivotal role. Whether you’re involved in lead scoring or any other binary classification system, understanding the intricacies of evaluation metrics is key. Among these, the ROC (Receiver Operating Characteristic) curve and its integral companion, AUC … Read more
You are in charge of the cake for a child’s birthday. You have decided the cake will have one candle for each year of their total age. They will only be able to blow out the tallest of the candles. Count how many candles are tallest. Example candles=[4,4,1,3] The maximum height candles are 4 units high. … Read more
Given five positive integers, find the minimum and maximum values that can be calculated by summing exactly four of the five integers. Then print the respective minimum and maximum values as a single line of two space-separated long integers. Example arr=[1,3,5,7,9] The minimum sum is 1+3+5+7=16 and the maximum sum is 3+5+7+9=24 . The function prints Function Description … Read more