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9 important plots in data science

Data Science Dojo

Explore, analyze, and visualize data using Power BI Desktop to make data-driven business decisions. Check out our Introduction to Power BI cohort. Gini Impurity vs. Entropy: These plots are critical in the field of decision trees and ensemble learning.

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Elevating business decisions from gut feelings to data-driven excellence

Dataconomy

These algorithms are carefully selected based on the specific decision problem and are trained using the prepared data. Machine learning algorithms, such as neural networks or decision trees, learn from the data to make predictions or generate recommendations.

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What is Data-driven vs AI-driven Practices?

Pickl AI

To confirm seamless integration, you can use tools like Apache Hadoop, Microsoft Power BI, or Snowflake to process structured data and Elasticsearch or AWS for unstructured data. Develop Hybrid Models Combine traditional analytical methods with modern algorithms such as decision trees, neural networks, and support vector machines.

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How to become a data scientist

Dataconomy

It involves developing algorithms that can learn from and make predictions or decisions based on data. Familiarity with regression techniques, decision trees, clustering, neural networks, and other data-driven problem-solving methods is vital. Tools like Tableau, Matplotlib, Seaborn, or Power BI can be incredibly helpful.

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Data Analysis vs. Data Visualization – More Than Just Pretty Charts

Pickl AI

Modeling: Build a logistic regression or decision tree model to predict the likelihood of a customer churning based on various factors. Tools Commonly Used Business Intelligence Platforms: Tableau, Microsoft Power BI, Qlik Sense, Google Data Studio (Looker Studio) Programming Libraries: Matplotlib, Seaborn (Python); ggplot2 (R); D3.js

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Data Scientist Salary in India’s Top Tech Cities

Pickl AI

Here is the tabular representation of the same: Technical Skills Non-technical Skills Programming Languages: Python, SQL, R Good written and oral communication Data Analysis: Pandas, Matplotlib, Numpy, Seaborn Ability to work in a team ML Algorithms: Regression Classification, Decision Trees, Regression Analysis Problem-solving capability Big Data: (..)

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Predicting the Future of Data Science

Pickl AI

Dive Deep into Machine Learning and AI Technologies Study core Machine Learning concepts, including algorithms like linear regression and decision trees. Learn to use tools like Tableau, Power BI, or Matplotlib to create compelling visual representations of data. Additionally, familiarity with cloud platforms (e.g.,