Tutorials :

Data Science Tools: Python, Pandas, Machine Learning, EDA

      Author: Delcan   |   26 June 2024   |   comments: 0

Data Science Tools: Python, Pandas, Machine Learning, EDA
Data Science Tools: Python, Pandas, Machine Learning, EDA
Published 6/2024
Created by Bluelime Learning Solutions
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 122 Lectures ( 8h 49m ) | 2.1 GB

Learn Data Science Skills with: Python, Pandas, NumPy, Matplotlib, Seaborn, Machine Learning, Data Prep, and EDA

What you'll learn:
Utilize essential data science libraries such as Pandas, NumPy, Matplotlib, and Seaborn.
Differentiate between structured and unstructured data.
Gain proficiency in Python programming language for data analysis.
Understand the fundamental concepts of data science.
Differentiate between data science, data engineering, and data analysis.
Recognize the applications and industry impact of data science.
Install Python and set up a development environment on Windows and macOS.
Familiarize with Jupyter Notebook and use it for interactive data analysis.
Explore and manipulate data using Pandas DataFrames.
Create and manipulate Pandas Series for efficient data handling.
Load datasets into Pandas and perform initial data inspection and cleaning.
Transform and analyze data using Pandas methods.
Visualize data using Matplotlib and Seaborn for insights and reporting.
Utilize statistical techniques for data exploration and hypothesis testing.
Define machine learning and its application in data science.
Understand supervised, unsupervised, and reinforcement learning techniques.
Preprocess data for machine learning models, including handling missing values and encoding categorical variables.
Build, train, and evaluate machine learning models using scikit-learn.
Measure model performance using metrics like accuracy, confusion matrix, and classification report.
Deploy a machine learning model for real-time predictions and understand model interpretability techniques.

Requirements:
Basic Computer Literacy
No prior programming experience required, but familiarity with the basics of programming concepts (e.g., variables, loops, conditional statements) is beneficial.
Access to a computer with internet connectivity.
Ability to install software, including Python and necessary libraries (installation instructions will be provided).
Willingness to learn and explore new tools and technologies (e.g., Jupyter Notebook).


https://www.udemy.com/course/data-science-tools-python-pandas-machine-learning-eda/


Data Science Tools: Python, Pandas, Machine Learning, EDA Fast Download
Data Science Tools: Python, Pandas, Machine Learning, EDA Full Download

free Data Science Tools: Python, Pandas, Machine Learning, EDA, Downloads Data Science Tools: Python, Pandas, Machine Learning, EDA, Rapidgator Data Science Tools: Python, Pandas, Machine Learning, EDA, Nitroflare Data Science Tools: Python, Pandas, Machine Learning, EDA, Mediafire Data Science Tools: Python, Pandas, Machine Learning, EDA, Uploadgig Data Science Tools: Python, Pandas, Machine Learning, EDA, Mega Data Science Tools: Python, Pandas, Machine Learning, EDA, Torrent Download Data Science Tools: Python, Pandas, Machine Learning, EDA, HitFile Data Science Tools: Python, Pandas, Machine Learning, EDA , GoogleDrive Data Science Tools: Python, Pandas, Machine Learning, EDA,  Please feel free to post your Data Science Tools: Python, Pandas, Machine Learning, EDA Download, Tutorials, Ebook, Audio Books, Magazines, Software, Mp3, Free WSO Download , Free Courses Graphics , video, subtitle, sample, torrent, NFO, Crack, Patch,Rapidgator, mediafire,Mega, Serial, keygen, Watch online, requirements or whatever-related comments here.





DISCLAIMER
None of the files shown here are hosted or transmitted by this server. The links are provided solely by this site's users. The administrator of our site cannot be held responsible for what its users post, or any other actions of its users. You may not use this site to distribute or download any material when you do not have the legal rights to do so. It is your own responsibility to adhere to these terms.

Copyright © 2018 - 2023 Dl4All. All rights reserved.