Python for Data Science and Machine Learning

在本课程您将学习：

下载和安装数据科学和机器学习所需的文件

所有关于Numpy：数组操作，切片，转置，以及它的所有功能等。。

如何使用Python进行数据科学和机器学习

学习使用Pandas进行数据分析

A-Z Pandas

探索性数据分析

基于数据科学和Ml问题的问题解决能力。

数据科学和机器学习所需的统计学

股票数据分析

使用不同的数据集并进行预测

应用决策树分类器、朴素贝叶斯等机器学习模型解决问题

理解回归和相关

建立回归模型进行房价预测

从图像中提取文本数据

Kmeans与层次聚类

Duration: 7h 3m | Video: .MP4, 1280×720 30 fps | Audio: AAC, 44.1 kHz, 2ch | Size: 2.48 GB
Genre: eLearning | Language: English

A Practical Approach Learn by Implementing

What you’ll learn
Downloading and Installing the required Files for Data Science and Machine learning
All about Numpy : array manipulation , slicing , transpose , and all functions of it etc..
How to Use Python for Data Science and Machine Learning
Learn to use Pandas for Data Analysis
A-Z pandas
Exploratory Data Analysis
Problem Solving Skills based on Data Science and Ml problems.
Statistics Required For Data Science and Machine Learning
Stock Data Analysis
Working with Different Datasets and Making Predictions
Applying Decision tree classifier , Naive bayes and other Machine Learning Models to solve the problems
Understanding Regression and Correlation
Building Regression Model to deal with house price prediction
Text Data Extraction from Image
Kmeans and Hierarchical Clustering etc..

Requirements
No prerequisites required anyone willing to learn can join

Description
This course is based on practical Approach towards Machine Learning and Data Science.

Starting from the basic python libraries and going to implement and perform more complex level predictions.

There is no prerequisite for this course but still you must go through the python basic documentation which you will get in this course material.

and you must have basic knowledge of python before starting with this course.

There will be some assignments based on data science which will include

stock analysis

text extraction

working on different data sets

applying different algorithms in an effective manner.

more

Here we explore different methods , libraries . make predictions , verify results and more .

Learn how to use

NumPy

Pandas

Seaborn

Matplotlib

Plotly

Scikit-Learn

Machine Learning

more!

This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science!

This will going to most effective and comprehensive course for data science aspirants

you will be able to think like a data wizard or data scientist.]

you will get the dataset from the course material and also its available on web i will show you have to download that also.

you will also get some good understanding of

data cleaning

data preprocessing

data methodologies

applying tests

etc

updates

CODES ALL UP TO DATE

Who this course is for:

Anyone interested in Machine Learning , Data Science.

Students who have at least high school knowledge in math and who want to start learning Machine Learning.

Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning.

Any people who are not that comfortable with coding but who are interested in Machine Learning and want to apply it easily on datasets.

Any students in college who want to start a career in Data Science.

Any data analysts who want to level up in Machine Learning.

Any people who are not satisfied with their job and who want to become a Data Scientist.

Any people who want to create added value to their business by using powerful Machine Learning tools.

Students in the field of Data Science

Any one who is willing to learn can join .

Who this course is for:
Python developers curious about Data Science
Anyone interested in Machine Learning , Data Science.
Students who have at least high school knowledge in math and who want to start learning Machine Learning.
Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning.
Any people who are not that comfortable with coding but who are interested in Machine Learning and want to apply it easily on datasets.
Any students in college who want to start a career in Data Science
Any data analysts who want to level up in Machine Learning.
Any people who are not satisfied with their job and who want to become a Data Scientist.
Any people who want to create added value to their business by using powerful Machine Learning tools.
Students in the field of Data Science
Any one who is willing to learn can join .