Welcome to my site, it’s all dedicated for Data Science. 🙂
I’d like to welcome you to keep in touch and we can share our knowledge in ML, DL, & AI.
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Data science is an interdisciplinary field that involves the extraction, analysis, interpretation, and visualization of data to uncover insights, make informed decisions, and solve complex problems. It combines elements of statistics, mathematics, computer science, and domain knowledge to extract meaningful information from data.
Data discovery refers to the process of exploring and analyzing data to gain insights, identify patterns, and discover valuable information within datasets.
Machine Learning (ML) is a subfield of artificial intelligence (AI) that focuses on the development of algorithms and models that enable computers to learn from data and make predictions or decisions without being explicitly programmed.
Deep Learning is a subfield of machine learning that focuses on developing and training artificial neural networks (ANNs) with multiple layers, enabling them to learn hierarchical representations of data.
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My most recent projects in data science and machine learning have been focused on leveraging the power of data to extract valuable insights and drive informed decision-making. Using advanced analytical techniques and machine learning algorithms, I have tackled complex problems across various domains.
Machine Learning
Random Forest is a popular machine learning algorithm that belongs to the family of ensemble learning methods.
Machine Learning
Logistic Regression is a popular statistical modeling technique used to analyze the relationship between a binary dependent variable (also called the response variable) and one or more independent variables (also called predictor or explanatory variables)
Machine Learning
The goal of this project is to optimize the detection and diagnoses of breast cancer at the early stage by using machine learning models.