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Data Science

Data science is an interdisciplinary field that combines techniques from statistics, mathematics, computer science, and domain expertise to extract knowledge and insights from data. It involves collecting, cleaning, and processing large datasets to uncover hidden patterns, trends, and valuable information.

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Machine Learning Optimization with Gradient Descent

Gradient Descent is optimization algorithm of find optimal solution to problems. In Machine Learning it is used to find optimal parameters of model to minimize cost function.

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3 min read
Data Science

Evaluate Machine Learning Performance

Evaluating Machine Learning performance is essential for selecting right model, tuning parameters, detecting overfitting/underfitting, and assesing the model generalization ability to new data (unseen data in training process).

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4 min read
Data Science

Machine Learning: Perceptron Classifier

Perceptron Classifier is one of the classification algorithms in machine learning. It is similar to linear regression model because it uses combination of features to predict.

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3 min read
Data Science

Machine Learning: Underfitting, Overfitting, and Generalization

Machine learning models aim for generalization to new data. Underfitting (too simple) and overfitting (too complex) hinder this. Achieving balance ensures effective, robust performance.

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3 min read
Data Science

Machine Learning: K-Means Clustering

K-Means is a popular clustering algorithm, simplifying data partitioning based on similarity for efficient pattern recognition in diverse applications.

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2 min read
Data Science

Machine Learning: Fundamental Concepts and Algorithms

The concepts of linear regression, classification, clustering, and Hidden Markov Model (HMM) represent different types of machine learning algorithms or models.

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2 min read
Data Science

Machine Learning: What are Tensors?

In machine learning, tensors are crucial multi-dimensional arrays for data representation and manipulation in diverse algorithms.

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2 min read
Data Science

Paradigms of Machine Learning

Machine learning encompasses supervised, unsupervised, reinforcement, semi-supervised, and self-supervised learning paradigms, each tailored for specific tasks and objectives.

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7 min read
Data Science

Exploring Search Algorithms: Uninformed and Informed Search

What is different uninformed and informed search for problem solving?

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3 min read
Data Science

Exploring Search Algorithms: Breadth First Search (BFS) VS Depth First Search (DFS)

Different between Breadth First Search (BFS) and Depth First Search (DFS).

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3 min read
Data Science