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Training & Visualizing a Decision Tree ,predicting and checking sensitivity

Ashish Dikshit
This course is no longer available. Find a similar course by searching these:
decision tree visualization decision tree guide decision tree learning decision tree training decision tree tutorial decision tree visualization

Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Useful for those who work with decision trees, such as data scientists, researchers, and business analysts
Teaches skills and knowledge that are highly relevant to industry
Taught by Ashish Dikshit, who is recognized for their work in decision trees
Develops core skills for data analysis and decision-making

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Training & Visualizing a Decision Tree ,predicting and checking sensitivity with these activities:
Interactive Decision Tree Tutorials
Supplement your learning with interactive tutorials, offering a practical and accessible way to grasp the fundamentals of Decision Trees.
Browse courses on Online Learning
Show steps
  • Explore online tutorials and simulations on Decision Tree concepts
  • Follow guided examples and practice building simple Decision Trees
Review 'Decision Trees for Data Mining and Machine Learning'
Gain a comprehensive understanding of Decision Trees through this foundational text, solidifying the theoretical basis for your learning.
View Data Mining on Amazon
Show steps
  • Read and summarize key chapters on Decision Tree algorithms and their applications
  • Work through examples and exercises provided in the book
Solving Decision Tree Exercises and Problems
Solidify your understanding of Decision Tree algorithms by engaging in targeted practice exercises, honing your problem-solving skills.
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  • Work through guided examples of Decision Tree construction
  • Attempt practice problems and exercises to test your comprehension
  • Review solutions and identify areas for improvement
Three other activities
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Show all six activities
Develop a Decision Tree Model for Predicting Customer Churn
Empower yourself to build and evaluate a Decision Tree model, gaining hands-on experience with a fundamental technique for predicting customer behavior.
Browse courses on Predictive Analytics
Show steps
  • Gather and preprocess a customer churn dataset
  • Identify and explore relevant features for the model
  • Train and evaluate the Decision Tree model
  • Interpret the model's predictions and evaluate its performance
Collaborative Decision Tree Analysis
Engage in peer-led discussions and collaborative problem-solving, fostering a deeper understanding of Decision Tree applications and enhancing your communication skills.
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Show steps
  • Join or form study groups to discuss Decision Tree concepts
  • Collaborate on building and evaluating Decision Tree models for real-world scenarios
  • Provide constructive feedback and learn from peers' perspectives
Visualizing Decision Tree Models
Deepen your understanding of Decision Tree models by visualizing them graphically, fostering a clear mental representation of their structure and behavior.
Browse courses on Data Visualization
Show steps
  • Choose appropriate visualization tools for Decision Trees
  • Create visual representations of Decision Trees from various datasets
  • Analyze and interpret the visualizations to gain insights into the model's decision-making process

Career center

Learners who complete Training & Visualizing a Decision Tree ,predicting and checking sensitivity will develop knowledge and skills that may be useful to these careers:
Data Scientist
A Data Scientist uses their knowledge of mathematics, statistics, and computing to gather and analyze large datasets. They then use that information to build models that help businesses solve problems. This course may be useful for someone who wants to become a Data Scientist because it provides a foundation in training and visualizing decision trees. This skill can be used to help build models that are more accurate and efficient.
See salaries and explore the career path for Data Scientist
Machine Learning Engineer
A Machine Learning Engineer designs and implements machine learning models. They use their knowledge of mathematics, statistics, and computing to develop models that can learn from data and make predictions. This course may be useful for someone who wants to become a Machine Learning Engineer because it provides a foundation in training and visualizing decision trees. This skill can be used to help build models that are more accurate and efficient.
See salaries and explore the career path for Machine Learning Engineer
Data Analyst
A Data Analyst gathers, analyzes, and interprets data to help businesses make better decisions. They use their knowledge of mathematics, statistics, and computing to identify trends and patterns in data. This course may be useful for someone who wants to become a Data Analyst because it provides a foundation in training and visualizing decision trees. This skill can be used to help identify trends and patterns in data more quickly and accurately.
See salaries and explore the career path for Data Analyst
Business Analyst
A Business Analyst helps businesses understand their data and make better decisions. They use their knowledge of mathematics, statistics, and computing to analyze data and make recommendations to businesses. This course may be useful for someone who wants to become a Business Analyst because it provides a foundation in training and visualizing decision trees. This skill can be used to help analyze data and make recommendations more quickly and accurately.
See salaries and explore the career path for Business Analyst
Statistician
A Statistician uses their knowledge of mathematics and statistics to collect, analyze, and interpret data. They use this information to help businesses and organizations make better decisions. This course may be useful for someone who wants to become a Statistician because it provides a foundation in training and visualizing decision trees. This skill can be used to help analyze data more quickly and accurately.
See salaries and explore the career path for Statistician
Financial Analyst
A Financial Analyst uses their knowledge of mathematics and statistics to analyze financial data and make recommendations to businesses. They use this information to help businesses make better decisions about investments and other financial matters. This course may be useful for someone who wants to become a Financial Analyst because it provides a foundation in training and visualizing decision trees. This skill can be used to help analyze financial data more quickly and accurately.
See salaries and explore the career path for Financial Analyst
Operations Research Analyst
An Operations Research Analyst uses their knowledge of mathematics and statistics to analyze data and make recommendations to businesses about how to improve their operations. They use this information to help businesses make better decisions about how to allocate resources and other operational matters. This course may be useful for someone who wants to become an Operations Research Analyst because it provides a foundation in training and visualizing decision trees. This skill can be used to help analyze data more quickly and accurately.
See salaries and explore the career path for Operations Research Analyst
Market Research Analyst
A Market Research Analyst uses their knowledge of mathematics and statistics to analyze data and make recommendations to businesses about how to market their products and services. They use this information to help businesses make better decisions about how to target their marketing efforts and other marketing-related matters. This course may be useful for someone who wants to become a Market Research Analyst because it provides a foundation in training and visualizing decision trees. This skill can be used to help analyze data more quickly and accurately.
See salaries and explore the career path for Market Research Analyst
Quantitative Analyst
A Quantitative Analyst uses their knowledge of mathematics and statistics to analyze data and make recommendations to businesses about how to invest their money. They use this information to help businesses make better decisions about how to allocate their resources and other investment-related matters. This course may be useful for someone who wants to become a Quantitative Analyst because it provides a foundation in training and visualizing decision trees. This skill can be used to help analyze data more quickly and accurately.
See salaries and explore the career path for Quantitative Analyst
Risk Analyst
A Risk Analyst uses their knowledge of mathematics and statistics to analyze data and make recommendations to businesses about how to manage their risks. They use this information to help businesses make better decisions about how to allocate their resources and other risk-related matters. This course may be useful for someone who wants to become a Risk Analyst because it provides a foundation in training and visualizing decision trees. This skill can be used to help analyze data more quickly and accurately.
See salaries and explore the career path for Risk Analyst
Actuary
An Actuary uses their knowledge of mathematics and statistics to analyze data and make recommendations to businesses about how to manage their risks. They use this information to help businesses make better decisions about how to allocate their resources and other risk-related matters. This course may be useful for someone who wants to become an Actuary because it provides a foundation in training and visualizing decision trees. This skill can be used to help analyze data more quickly and accurately.
See salaries and explore the career path for Actuary
Data Visualization Specialist
A Data Visualization Specialist uses their knowledge of design and technology to create visual representations of data. They use this information to help businesses communicate their data more effectively. This course may be useful for someone who wants to become a Data Visualization Specialist because it provides a foundation in training and visualizing decision trees. This skill can be used to help create visual representations of data that are more clear and concise.
See salaries and explore the career path for Data Visualization Specialist
User Experience Designer
A User Experience Designer uses their knowledge of design and technology to create user interfaces that are easy to use and understand. They use this information to help businesses create products and services that are more user-friendly. This course may be useful for someone who wants to become a User Experience Designer because it provides a foundation in training and visualizing decision trees. This skill can be used to help create user interfaces that are more intuitive and efficient.
See salaries and explore the career path for User Experience Designer
Software Engineer
A Software Engineer uses their knowledge of computer science to design, develop, and maintain software applications. They use this information to help businesses create products and services that are more efficient and effective. This course may be useful for someone who wants to become a Software Engineer because it provides a foundation in training and visualizing decision trees. This skill can be used to help design and develop software applications that are more efficient and effective.
See salaries and explore the career path for Software Engineer

Reading list

We've selected ten books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Training & Visualizing a Decision Tree ,predicting and checking sensitivity.
Cover image
The Elements of Statistical Learning
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Comprehensive reference on statistical learning methods, providing a deep understanding of the theoretical foundations and practical applications of these techniques. It covers a wide range of topics, including linear and nonlinear regression, classification, and clustering, and provides numerous examples and case studies to illustrate the concepts.
The Elements of Statistical Learning: Data Mining,...
Hardcover
$$$
The Elements of Statistical Learning: Data Mining,...
Hardcover
$$$
The Elements of Statistical Learning: Data Mining,...
Kindle Edition
$$$
Pattern Recognition and Machine Learning
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Provides a comprehensive overview of pattern recognition and machine learning, covering a wide range of topics from supervised and unsupervised learning to Bayesian inference and neural networks. It valuable resource for those looking to gain a deeper understanding of the theoretical foundations of machine learning.
Pattern Recognition and Machine Learning...
Hardcover
$$$
Pattern Recognition and Machine Learning...
Paperback
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Pattern Recognition and Machine Learning (text...
Unknown Binding
$$$$
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Deep Learning
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Provides a comprehensive overview of deep learning, covering a wide range of topics from neural networks to convolutional neural networks and recurrent neural networks. It valuable resource for those looking to gain a deeper understanding of the theoretical foundations and practical applications of deep learning.
Deep Learning
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Deep Learning (Adaptive Computation and Machine...
Hardcover
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Deep Learning (Adaptive Computation and Machine...
Kindle Edition
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Speech and Language Processing. An Introduction to...
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Provides a comprehensive overview of speech and language processing, covering a wide range of topics from speech recognition to natural language processing. It valuable resource for those looking to gain a deeper understanding of the theoretical foundations and practical applications of speech and language processing.
Speech and Language Processing An Introduction to...
Paperback
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Probabilistic Machine Learning
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Provides a comprehensive overview of machine learning from a probabilistic perspective, covering topics such as Bayesian inference, graphical models, and deep learning. It valuable resource for those looking to gain a deeper understanding of the theoretical foundations of machine learning.
Probabilistic Machine Learning: Advanced Topics...
Hardcover
$$$$
Cover image
Computer Vision
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Provides a comprehensive overview of computer vision, covering a wide range of topics from image processing to object recognition and tracking. It valuable resource for those looking to gain a deeper understanding of the theoretical foundations and practical applications of computer vision.
Computer Vision
Paperback
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Computer Vision
Kindle Edition
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Cover image
Data Mining
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Provides a comprehensive overview of data mining, covering a wide range of topics from data preparation to model selection and evaluation. It valuable resource for those looking to gain a deeper understanding of the theoretical foundations and practical applications of data mining.
Data Mining: Practical Machine Learning Tools and...
Paperback
$$$
DATA MINING, 4TH EDITION
Paperback
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Data Mining: Practical Machine Learning Tools and...
Kindle Edition
$$
Cover image
Natural Language Processing with Python
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Provides a practical introduction to natural language processing using Python, covering a wide range of topics from text processing to machine learning. It valuable resource for those looking to apply natural language processing techniques to real-world problems.
Natural Language Processing with Python: Analyzing...
Paperback
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Natural Language Processing with Python: Analyzing...
Kindle Edition
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Cover image
Hands-On Machine Learning with Scikit-Learn, Keras,...
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Provides a practical introduction to machine learning using Python libraries such as scikit-learn, Keras, and TensorFlow. It covers a wide range of topics from data preparation to model selection and evaluation, and provides hands-on examples and exercises to reinforce learning.
Hands-On Machine Learning with Scikit-Learn, Keras,...
Paperback
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Hands-On Machine Learning with Scikit-Learn, Keras,...
Paperback
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Hands-On Machine Learning with Scikit-Learn, Keras,...
Kindle Edition
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Cover image
Machine Learning for Hackers
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Provides a practical introduction to machine learning for hackers, covering a wide range of topics from data preparation to model selection and evaluation. It valuable resource for those looking to apply machine learning techniques to real-world problems.
Machine Learning for Hackers: Case Studies and...
Paperback
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Machine Learning for Hackers: Case Studies and...
Kindle Edition
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Time
2 hours
Via
Coursera
Institution
Coursera Project Network
Instructor
Ashish Dikshit
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Useful for those who work with decision trees, such as data scientists, researchers, and business analysts
Teaches skills and knowledge that are highly relevant to industry
Taught by Ashish Dikshit, who is recognized for their work in decision trees
Develops core skills for data analysis and decision-making
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