Python Machine Learning With Data analysis data Science Training Course in Udaipur
Python Machine Learning With Data analysis data Science Training Course in Udaipur
Module 1:- Course Intro With Python Data Analysis
Module 2:-Python Learning Intro to numpy
Module 3:- Python Pandas
Module 4:- Working with data
Module 5:- Data Visualizations
Module 6:-Introduction to Machine Learning
Module 7:- Regression
Module 8:- Classification
Module 9:- Unsupervised Learning
Python Machine Learning With Data Analysis Data Science Training Course at KEEN INFOTECH ?
Course Intro With Data Analysis
-
Installation Setup and Overview
-
IDEs and Course Resources
-
iPython/Jupyter Notebook Overview
Learning Intro to numpy
- Intro to numpy
- Creating arrays
- Using arrays and scalars
- Indexing Arrays
- Array Transposition
- Universal Array Function
- Array Processing
- Array Input and Output
Python Machine Learning Pandas
- Series
- DataFrames
- Index objects
- Reindex
- Drop Entry
- Selecting Entries
- Data Alignment
- Rank and Sort
- Summary Statistics
- Missing Data
- Index Hierarchy
Python Working with data
- Reading and Writing Text Files
- JSON with Python
- HTML with Python
- Microsoft Excel files with Python
- Merge ,Merge on Index
- Concatenate
- Combining DataFrames
- Reshaping Pivoting
- Duplicates in DataFrames
- Mapping Replace
- Rename Index
- Binning,Outliers,Permutation
- GroupBy on DataFrames
- GroupBy on Dict and Series
- Splitting Applying and Combining
- Cross Tabulation
Python Data Visualization
- Installing Seaborn
- Histograms
- Kernel Density Estimate Plots
- Combining Plot Styles
- Box and Violin Plots
- Regression Plots
- Heatmaps and Clustered Matrices
Introduction to Machine Learning
- Applications of Machine Learnings
- Supervised vs Unsupervised Learning
- Python libraries suitable for Machine Learning
Python Regression
- Linear Regression
- Non-linear Regression
- Model evaluation methods
Python Classification
- K-Nearest Neighbour
- Decision Trees
- Logistic Regression
- Support Vector Machines
- Model Evaluation
Python Unsupervised Learning
- K-Means Clustering
- Hierarchical Clustering
- Density-Based Clustering
Overview About Python Machine Learning Data Analysis
Welcome to Data Analysis in Python!
Python is an increasingly popular tool for data analysis. In recent years, a number of libraries have reached maturity, allowing R and Stata users to take advantage of the beauty, flexibility, and performance of Python without sacrificing the functionality these older programs have accumulated over the years.Python Machine Learning With Data Analysis Training in Udaipur Rajasthan
This site is designed to offer an introduction to Python specifically tailored for social scientists and people doing applied data analysis – users with little or no serious programming experience who just want to get things done, and who have experience with programs like R and Stata but are anxious for something better.
Python Machine Learning With Data Analysis Data Science Training Course at KEEN INFOTECH ?
Course Intro With Data Analysis
- Installation Setup and Overview
- IDEs and Course Resources
- iPython/Jupyter Notebook Overview
Learning Intro to numpy
- Intro to numpy
- Creating arrays
- Using arrays and scalars
- Indexing Arrays
- Array Transposition
- Universal Array Function
- Array Processing
- Array Input and Output
Python Machine Learning Pandas
- Series
- DataFrames
- Index objects
- Reindex
- Drop Entry
- Selecting Entries
- Data Alignment
- Rank and Sort
- Summary Statistics
- Missing Data
- Index Hierarchy
Python Working with data
- Reading and Writing Text Files
- JSON with Python
- HTML with Python
- Microsoft Excel files with Python
- Merge ,Merge on Index
- Concatenate
- Combining DataFrames
- Reshaping Pivoting
- Duplicates in DataFrames
- Mapping Replace
- Rename Index
- Binning,Outliers,Permutation
- GroupBy on DataFrames
- GroupBy on Dict and Series
- Splitting Applying and Combining
- Cross Tabulation
Python Data Visualization
- Installing Seaborn
- Histograms
- Kernel Density Estimate Plots
- Combining Plot Styles
- Box and Violin Plots
- Regression Plots
- Heatmaps and Clustered Matrices
Introduction to Machine Learning
- Applications of Machine Learnings
- Supervised vs Unsupervised Learning
- Python libraries suitable for Machine Learning
Python Regression
- Linear Regression
- Non-linear Regression
- Model evaluation methods
Python Classification
- K-Nearest Neighbour
- Decision Trees
- Logistic Regression
- Support Vector Machines
- Model Evaluation
Python Unsupervised Learning
- K-Means Clustering
- Hierarchical Clustering
- Density-Based Clustering
Overview About Python Machine Learning Data Analysis
Welcome to Data Analysis in Python! Python is an increasingly popular tool for data analysis. In recent years, a number of libraries have reached maturity, allowing R and Stata users to take advantage of the beauty, flexibility, and performance of Python without sacrificing the functionality these older programs have accumulated over the years.Python Machine Learning With Data Analysis Training in Udaipur Rajasthan
This site is designed to offer an introduction to Python specifically tailored for social scientists and people doing applied data analysis – users with little or no serious programming experience who just want to get things done, and who have experience with programs like R and Stata but are anxious for something better.