Este chollo ya no está disponible
Curso gratis de Python de 20 horas (udemy, inglés)
364° Agotado

Curso gratis de Python de 20 horas (udemy, inglés)

GRATIS184,99€Ofertas Udemy
7
Publicado el 10 de marzo

¡Oops! Este chollo parece estar ya agotado... Aquí tienes unas opciones que te pueden interesar:

Descubre uno de los lenguajes de programación más populares y aprende a programar a tu propio ritmo.

Python es el lenguaje ideal para comenzar. No sólo debido a su sencillez, sino también gracias a su versatilidad y potencial de uso, que lo convierten en uno de los dos lenguajes más usados a nivel empresarial.

Introduction
  • Welcome!!!
  • Introduction to PythonVista previa
  • How to Install Python on Windows
Python Basic Programming
  • Variables in Python - Tokens in Python
  • Operators in PythonVista previa
  • Data types in Python with Example (1)
  • Data types in Python with Example (2)
  • Flow Control in Python
  • How to Create Functions in Python
  • Lambda in Python
  • File Handling in Python
OOPs
  • introduction to OOP
  • classes and objectsVista previa
  • __init__()
  • demo test
  • Inheritance In Python
  • Inheritance supper function
  • Overriding and Overloading
  • encapsulation
  • Private Method
  • Polymorphism
Numpy
  • Working File
  • Numpy List and Array
  • Numpy dtype and shape
  • Numpy np.nan and np.inf
  • Numpy Statistical operations
  • Numpy sequence and repetitions
  • random numbers
  • more about numpy
  • read and write csv file
  • concat with row and col wise
  • sort a numpy array
  • working with dates
  • Numpy Advanced Function - vectorizeVista previa
Matplotlib
  • Working File
  • Introduction to this module
  • Matplotlib getting started
  • SubplotVista previa
  • objet oriented plots
  • Subplots
  • change figure size
  • legend label and name
  • style and color
  • plot range
  • types of plots
  • log scale
  • ticks
  • formatterVista previa
Panda
  • Introduction to Panda
  • series object Panda
  • DataFrame in Panda
  • merge join and concatenate
  • importing and analyzing the Dataset
  • cleaning the Dataset
Seaborn
  • Working File
  • introduction to Seaborn
  • import data
  • relplot part 1
  • relplot part 2
  • relplot part 3
  • relplot part 4
  • relplot part 5
  • lineplot
  • scatterplot
  • catplot
  • boxplot
  • boxenplotVista previa
  • violin
  • barplot and
  • Visualizing Distribution of the Data
  • Linear Regression and Relationship (regplot and lmplot)
  • Controlling Ploted Figure Aesthetics
Data Visualization - Plotly and Cufflinks
  • Working File
  • introduction
  • imports and Set-up
  • working with plotly
  • line plot
  • scatter plot
  • bar plot
  • box plot
  • area
  • 3D surfaceVista previa
  • spread
  • histogram
  • bubble
  • heatmap
Data Visualization in Panda
  • Working File
  • introduction and agenda
  • import data frame
  • line plot
  • bar plot
  • histogramVista previa
  • box plot
  • area plot
  • scatter plot
  • hexbin plot
  • pie plot
  • scatter_matrix plot
Introduction to Machine Learning
  • introduction to Machine Learning
Linear Regression on Boston Housing Dataset
  • work file
  • Linear Regression agenda
  • introduction to Linear Regression
  • Implimentation with sklearn
  • Lets get started
  • Understand your data
  • Data Visualization
  • Pairplot and Corrmat of correlated data
  • Shuffle and Split DataVista previa
  • Lets train the mode
  • Defining performance metrics
  • Regression Evaluation Metrics
  • Store feature performance
  • regression plot of the features correlated
  • find out other combination of columns to get better accuracy with > 60%Vista previa
  • find out other combination of columns to get better accuracy > 70%
  • select only RM feature
  • find out other combination of columns to get better accuracy > 40%
  • understand what is Normalization and Standardization
  • Defining performance metrics
Logistic Regression Titanic Dataset part 1
  • work file
  • Logistic Regression agenda
  • what is Logistic Regression
  • build a model which can predict if a passenser is gonna survive
  • Data understanding
  • Analysing EmbarkedVista previa
  • convert categorical data into numerical data
  • Build Logistic Regression Mode
Logistic Regression Titanic Dataset Part 2
  • agenda
  • Recursive Feature Elimination
  • Accuracy, F1-Score, P, R, AUC_ROC curve
K Nearest Neighbors : KNN algorithm
  • work file
  • KNN algorithm agenda
  • How does the KNN algorithm work
  • Classifier Building in Python and Scikit-learn
  • Generating Model
  • standardization in sklearn
  • Parameter Tuning with Cross ValidationVista previa
Support Vector Machines (SVM)
  • Working File
  • SVM agenda
  • What is Support Vector Machines (SVM)
  • Build Model in sklearn
  • Standardization
  • Split the data and build the model
  • Polynomial Kernel and Sigmoid KernelVista previa
Decision Tree Classifier and Regressor
  • Working File
  • Decision Tree Classifier and Regressor agenda
  • Decision Tree theory
  • Decision Tree Regressor
  • Decision Tree as a ClassifierVista previa
Random Forest Classifier and Regressor
  • Working File
  • Random Forest Classifier and Regressor agenda
  • What is Random Forest
  • Random Forest as a Regression
  • Random Forest as a Classifier with iris dataset
K-Mean Clustering Algorithm
  • Working File and data
  • K-Mean Clustering Algorithm agenda
  • what is K-Mean Clustering
  • Dataset and Problem Understanding
  • Do clustering
  • How do I choose right value of k
  • Use Iris datase
Python Principal Component Analysis (PCA)
  • Working File
  • Principal Component Analysis agenda
  • what is Principal Component Analysis
  • working with an example of PCA
Ensemble Learning
  • Working File
  • Ensemble Learning agenda
  • What is Ensemble Learning
  • working with an example
Learning Curve
  • Working File
  • what is Learning Curve
  • working with an example
Python Interview Questions
  • Basic Questions
  • Questions on OOPS
  • Questions on NumPy
  • Questions on Pandas
  • File Handling in Python
  • Lambda Function in Python
  • Questions on Matplotlib
  • Module in Python
  • Random Questions
  • Machine Learning with Python
Actualizaciones de la comunidad
Ofertas UdemyCupones Udemy

Categorías

7 comentarios
Buenos dias compi ++
Gracias +++
Gracias.
Muchas gracias!
Muchas gracias
pone que el código ha expirado...
expirado...
Publica un comentario
Avatar
@
    Texto