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2021-04-06 09:20:20
30-Day Money-Back Guarantee
IT & Software IT Certification Data Science

Python for Data Science and Machine Learning

A Practical Approach Learn by Implementing
New
Rating: 4.2 out of 54.2 (56 ratings)
14,846 students
Created by Kumar Rajmani Bapat
Last updated 3/2021
English
30-Day Money-Back Guarantee

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
  • willingness to learn

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 .


For Financial Support :

Indian's can contribute at  upi id- k.rajmani@paytm

and Foreigner's / NRI's  can contribute using PayPal

on below email id-

paramsiddha@gmail.com

please contribute to support the efforts for developing new exclusive resources and contents like this

support so that will continue bringing more such courses to stay productive and updated with latest trends in Data Science and Machine Learning.

Also give your feedback and rating.

Thank you.

..................................................................




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 .

Course content

8 sections • 19 lectures • 7h 3m total length

  • Preview17:28

  • Numpy : Numpy functions , Array operations , more
    35:30
  • Numpy Part 2
    26:27
  • # Problem statement # # The function getMinMax(arr) needs to be implemented.
    1 question

  • Pandas Imp Doc
    00:36
  • Pandas theory
    03:50
  • Pandas part 1
    35:54
  • Pandas part 2
    01:00:52

  • Statistics For Data Science and ML
    24:46

  • Stock Data Analysis
    26:35

  • Titanic Dataset Predictions
    56:26
  • Weather Data Analysis
    09:30
  • Naive Bayes Classifier
    05:43
  • Applying Naive Bayes classifier on Iris Data
    11:01
  • Naive Bayes Classifier Iris Data Part 2
    10:28
  • Preview00:10
  • Understanding Regression and Correlation and Implementing T statistic
    29:03
  • House data Prediction and Analysis using Linear Regression
    28:09

  • Text Extraction from Image
    20:07

  • Kmeans and Hierarchical
    14:48

Instructor

Kumar Rajmani Bapat
Google Certified Python Expert | Google Chrome Extension Dev
Kumar Rajmani Bapat
  • 4.0 Instructor Rating
  • 117 Reviews
  • 17,445 Students
  • 2 Courses

Hello World.....

I am a self driven motivated individual with an ability to grow myself and others.

My field of Specialization is Data Science and Machine Learning .

I have hands on experience in Analyzing Data Making Predictions

using Python and R .

I also want to learn cloud to deploy my projects there.

And if you like may contents and Exclusive Materials and Documentation you can provide your Rating and Feedback.

And

For Financial Support :

Indian's can contribute at  upi id- k.rajmani@paytm

and Foreigner's / NRI's  can contribute using PayPal

on below email id-

paramsiddha@gmail.com

please contribute to support the efforts for developing new exclusive resources and contents like this

support so that will continue bringing more such courses to stay productive and updated with latest trends in Data Science and Machine Learning.

Also give your feedback and rating.

Thank you.




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