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Python's collections module implements specialized container datatypes providing alternatives to Python’s general purpose built-in containers, dict, list, set, and tuple. This module has the following containers: 11. Counter() 22. namedtuple() 33. deque() 44. defaultdict() 55. OrderedDict() 66. UserDict() 77. …
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Decision Tree, Random Forest (RF), and Gradient Boosting (GB) are three popular algorithms used for supervised learning tasks such as classification and regression. In this blog, we will compare these three algorithms in terms of their features, performance, and usability. Decision Tree is a simple and intuitive …
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Security Linux tends to be a highly reliable and secure system than any other operating system (OS). Linux and Unix-based OS have fewer security flaws, as many developers constantly review the code. And anyone has access to its source code. So, you won’t need any anti-virus software to protect your PC from malware and …
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Word embedding is a technique in natural language processing (NLP) where words are represented as vectors of real numbers. This allows words with similar meanings to have similar representation, and can be used in various NLP tasks such as machine translation and text classification. There are several different …
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Lambda The Lambda function, also known as an anonymous or inline function, is a way to create a function without giving it a name. This can be useful when you need to define a function that will only be used once, or when you want to pass a function as an argument to another function. Here is an example of using a …
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Recurrent Neural Network A recurrent neural network (RNN), is a type of neural network that can process sequential data, like text, audio, or time series data. Here's how it works: first, the RNN takes in some input data, which could be a word in a sentence, a sound wave from an audio recording, or a measurement from a …
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Bit Manipulation Bit manipulation is a technique used in computer science to manipulate data at the level of its binary representation. This can be useful for a variety of tasks, such as low-level optimization, data compression, and cryptography. At its core, bit manipulation involves working with individual bits, …
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Very deep neural networks with a massive number of parameters are very robust machine learning systems. But, in this type of huge network, overfitting is a common serious problem. Learning how to deal with overfitting is essential to mastering machine learning. The fundamental issue in machine learning is the tension …
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Cleaning text for natural language processing (NLP) tasks is an important step that can help improve the performance of your model. In this blog post, we will discuss some common text cleaning techniques and how to apply them to your text data. The first step in cleaning text for NLP is to remove any noisy or …
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Dynamic programming is a method for solving complex problems by breaking them down into smaller subproblems. It is a mathematical optimization technique that is mainly used for solving problems that exhibit the properties of overlapping subproblems and optimal substructure. The basic idea behind dynamic programming is …
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Let's first understand what is Threading: Threading Threading is a technique for writing computer programs that run concurrently, or at the same time, in order to maximize the use of the available processing power. In other words, threading allows you to run multiple tasks within a single process, with each task …
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There are several different types of recommender systems, each with its own unique characteristics and applications. Some of the most commonly used types of recommender systems include: Content-based recommender systems: These systems recommend items to users based on the characteristics of the items themselves. For …
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Decorator is a design pattern to extend the functionality of a function without modifying the structure of the original function. Decorators are usually applied to functions using the @decorator syntax, immediately before the function definition. Example of how to use a decorator to extend the functionality of a …
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Breadth-first search (BFS) and depth-first search (DFS) are two algorithms for traversing graphs. These algorithms are used to search for specific nodes or to find the shortest path between two nodes in a graph. BFS The breadth-first search (BFS) algorithm is a graph traversal algorithm that explores all of the …
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