Remove Big Data Remove Decision Trees Remove Natural Language Processing
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How to become a data scientist – Key concepts to master data science

Data Science Dojo

Algorithms: Decision trees, random forests, logistic regression, and more are like different techniques a detective might use to solve a case. Overfitting and Underfitting: These are common problems in machine learning, like getting too caught up in small details or missing the big picture.

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Introduction to applied data science 101: Key concepts and methodologies 

Data Science Dojo

It leverages algorithms to parse data, learn from it, and make predictions or decisions without being explicitly programmed. From decision trees and neural networks to regression models and clustering algorithms, a variety of techniques come under the umbrella of machine learning.

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How to become a data scientist – Key concepts to master data science

Data Science Dojo

Algorithms: Decision trees, random forests, logistic regression, and more are like different techniques a detective might use to solve a case. Overfitting and Underfitting: These are common problems in machine learning, like getting too caught up in small details or missing the big picture.

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Training Sessions Coming to ODSC APAC 2023

ODSC - Open Data Science

Big Data Analysis with PySpark Bharti Motwani | Associate Professor | University of Maryland, USA Ideal for business analysts, this session will provide practical examples of how to use PySpark to solve business problems. Finally, you’ll discuss a stack that offers an improved UX that frees up time for tasks that matter.

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Unravelling the Buzzwords: Artificial Intelligence vs Deep Learning Explained

Pickl AI

Language Understanding: Processing and interpreting human language (Natural Language Processing – NLP). AI is a broad field focused on simulating human intelligence, encompassing techniques like decision trees and rule-based systems. This is a classic Deep Learning example.

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Maximizing SaaS application analytics value with AI

IBM Journey to AI blog

Given the volume of SaaS apps on the market (more than 30,000 SaaS developers were operating in 2023) and the volume of data a single app can generate (with each enterprise businesses using roughly 470 SaaS apps), SaaS leaves businesses with loads of structured and unstructured data to parse. What are application analytics?

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Data science vs. machine learning: What’s the difference?

IBM Journey to AI blog

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? Python is the most common programming language used in machine learning.