lovewarez
13 diciembre 2020, 23:34
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Data Analysis with Machine Learning & Data Visualization
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: aac, 44100 Hz
Language: English | SRT | Size: 4.36 GB | Duration: 9h 56m
What you'll learn
The course provides path to start career in Data Analysis and Data Science
Problem Solving Approach
Impress interviewers by showing an understanding of the Data Analysis withMachine Learning Algorithm concept
Python Basic to Advance Concept with Numpy, Pandas, Matplotlib, Seaborn, Plotly Library
Scikit Learn Library in Depth
Data Analysis with Machine Learning Algorithms such as Linear, Logistic, SVM, KNN, K Mean, Naïve Bayes, Decision Tree and Random Forest
Machine Learning Types Such as Supervise Learning, Unsupervised Learning
Data Analysis Case Study
Requirements
It start with Basics
Only a passion for Learning
All software used in this course is either available for Free or as a Demo version
This course is intended for absolute beginners in programming
Description
This Course will design to understand Data Visualization and Data Analysis with Machine Learning Algorithms with case Studies.
Data Analysis with Machine Learning Algorithms such as Linear Regression, Logistic Regression, SVM, K Mean, KNN, Naïve Bayes, Decision Tree and Random Forest are covered.
The course provides path to start career in Data Analysis. Importance of Data, Collection of Data with Case Study is covered.
Machine Learning Types such as Supervise Learning, Unsupervised Learning, are also covered. Machine Learning concept such as Train Test Split, Machine Learning Models, Model Evaluation are also covered.
Who this course is for:
The course is ideal for beginners, as it starts from the fundamentals and gradually builds up your skills in Data Analysis
People interested to learn Data Analysis with Machine Learning Algorithms using Scikit Learning Library and Python
https://www.udemy.com/course/data-analysis-with-machine-learning-data-visualization/
***Contenido oculto. Abra la versión completa del tema para visualizar los enlaces.***
Data Analysis with Machine Learning & Data Visualization
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: aac, 44100 Hz
Language: English | SRT | Size: 4.36 GB | Duration: 9h 56m
What you'll learn
The course provides path to start career in Data Analysis and Data Science
Problem Solving Approach
Impress interviewers by showing an understanding of the Data Analysis withMachine Learning Algorithm concept
Python Basic to Advance Concept with Numpy, Pandas, Matplotlib, Seaborn, Plotly Library
Scikit Learn Library in Depth
Data Analysis with Machine Learning Algorithms such as Linear, Logistic, SVM, KNN, K Mean, Naïve Bayes, Decision Tree and Random Forest
Machine Learning Types Such as Supervise Learning, Unsupervised Learning
Data Analysis Case Study
Requirements
It start with Basics
Only a passion for Learning
All software used in this course is either available for Free or as a Demo version
This course is intended for absolute beginners in programming
Description
This Course will design to understand Data Visualization and Data Analysis with Machine Learning Algorithms with case Studies.
Data Analysis with Machine Learning Algorithms such as Linear Regression, Logistic Regression, SVM, K Mean, KNN, Naïve Bayes, Decision Tree and Random Forest are covered.
The course provides path to start career in Data Analysis. Importance of Data, Collection of Data with Case Study is covered.
Machine Learning Types such as Supervise Learning, Unsupervised Learning, are also covered. Machine Learning concept such as Train Test Split, Machine Learning Models, Model Evaluation are also covered.
Who this course is for:
The course is ideal for beginners, as it starts from the fundamentals and gradually builds up your skills in Data Analysis
People interested to learn Data Analysis with Machine Learning Algorithms using Scikit Learning Library and Python
https://www.udemy.com/course/data-analysis-with-machine-learning-data-visualization/
***Contenido oculto. Abra la versión completa del tema para visualizar los enlaces.***