Udemy - Data science, Analytics and AI Real world Project using Python

  • CategoryOther
  • TypeTutorials
  • LanguageEnglish
  • Total size3.4 GB
  • Uploaded Byfreecoursewb
  • Downloads65
  • Last checkedApr. 11th '22
  • Date uploadedApr. 08th '22
  • Seeders 8
  • Leechers11

Infohash : 2567C07C1A102561A20671C4B31F9E009543C232

Data science, Analytics & AI Real world Project using Python



https://DevCourseWeb.com

Last Update: 3/2022
Duration: 6h 53m | Video: .MP4, 1280x720 30 fps | Audio: AAC, 48 kHz, 2ch | Size: 3.39 GB
Genre: eLearning | Language: English

Master AI , Data Analytics , Machine Learning & Data Sceince by solving Real-Life Analytics Problems using Python !
What you'll learn:
Go from zero to hero in Entire Pipeline of AI/Data Science/Machine learning from Data Collection to building a Machine Learning Model
Various Feature Engineering Techniques & how to apply it in Real-World
How to Approach a problem in Real-world..
Solve any problem in your business, job or in real-time with powerful Data Sceince & Machine Learning algorithms
Case studies
Requirements
Basic knowledge of Python programming is recommended.
Description

This is the first course that gives hands-on Data Science, Analytics & AI Real world Projects using Python..

This is a practical course, the course I wish I had when I first started learning Data Science.
It focuses on understanding all the basic theory and programming skills required as a Data Scientist, but the best part is that it has Practical Case Studies covering so many common business problems faced by Data Scientists in the real world.

Files:

[ DevCourseWeb.com ] Udemy - Data science, Analytics and AI Real world Project using Python
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1. Welcome to this course !
    • 1. Introduction to course & its benefits.mp4 (42.2 MB)
    • 1. Introduction to course & its benefits.srt (7.2 KB)
    • 2. Utilize QnA Section , (Golden Opportunity ).mp4 (9.4 MB)
    • 2. Utilize QnA Section , (Golden Opportunity ).srt (2.6 KB)
    • 3. How to follow this course - must watch !.mp4 (15.9 MB)
    • 3. How to follow this course - must watch !.srt (3.7 KB)
    • 4. Introduction to Jupyter Notebook.mp4 (43.4 MB)
    • 4. Introduction to Jupyter Notebook.srt (8.1 KB)
    10. Machine Learning
    • 1. Lecture 36.mp4 (109.6 MB)
    • 1. Lecture 36.srt (20.6 KB)
    11. Hypertuning of Machine Learning Model
    • 1. Lecture 37.mp4 (88.3 MB)
    • 1. Lecture 37.srt (15.8 KB)
    • 2. Lecture 38.mp4 (106.6 MB)
    • 2. Lecture 38.srt (17.9 KB)
    • 3. Lecture 39.mp4 (73.2 MB)
    • 3. Lecture 39.srt (12.4 KB)
    2. Understanding the business problem
    • 1. Datasets & Resources.html (0.2 KB)
    3. Data Analysis & Basic stats
    • 1. Perform Basic Stats on Data...mp4 (62.4 MB)
    • 1. Perform Basic Stats on Data...srt (13.5 KB)
    • 2. Lets Understand more about data !.mp4 (71.9 MB)
    • 2. Lets Understand more about data !.srt (13.5 KB)
    • 3. Checking for Duplicates questions in our data !.mp4 (44.6 MB)
    • 3. Checking for Duplicates questions in our data !.srt (8.7 KB)
    • 4. Finding occurrences of each question...mp4 (53.6 MB)
    • 4. Finding occurrences of each question...srt (10.4 KB)
    • 5. Lets perform Text Analysis...mp4 (94.7 MB)
    • 5. Lets perform Text Analysis...srt (14.5 KB)
    • 6. Lets perform Semantic Analysis...mp4 (78.6 MB)
    • 6. Lets perform Semantic Analysis...srt (12.4 KB)
    4. Feature Extraction for Data Science
    • 1. find frequency of questions-ID.mp4 (62.1 MB)
    • 1. find frequency of questions-ID.srt (11.3 KB)
    • 2. Finding Length of questions.mp4 (86.5 MB)
    • 2. Finding Length of questions.srt (13.0 KB)
    • 3. How to Find common words in 2 strings...mp4 (102.9 MB)
    • 3. How to Find common words in 2 strings...srt (16.9 KB)
    • 4. How to Find Total Words in 2 strings...mp4 (72.4 MB)
    • 4. How to Find Total Words in 2 strings...srt (10.6 KB)
    • 5. Lets Create some features using basic featurization...mp4 (45.8 MB)
    • 5. Lets Create some features using basic featurization...srt (7.7 KB)
    • 6. Analysing distribution of data ( Basic EDA).mp4 (96.0 MB)
    • 6. Analysing distribution of data ( Basic EDA).srt (15.4 KB)
    • 7. Finding Boxplot & Violinplot of data ( Basic EDA).mp4 (131.5 MB)
    • 7. Finding Boxplot & Violinplot of data ( Basic EDA).srt (18.8 KB)
    5. Data Pre-preocessing For Data ScienceML
    • 1. How to Overcome with the contractions of data !.mp4 (92.6 MB)
    • 1. How to Overcome with the contractions of data !.srt (17.4 KB)
    • 2. How to remove special characters from data.mp4 (110.8 MB)
    • 2. How to remove special characters from data.srt (15.8 KB)
    • 3. Lets Remove Extra White-spaces in data...mp4 (45.7 MB)
    • 3. Lets Remove Extra White-spaces in data...srt (6.7 KB)
    6. String matching in MLNLP
    • 1. String Matching using fuzz ratio.mp4 (76.1 MB)
    • 1. String Matching using fuzz ratio.srt (14.4 KB)
    • 2. String Matching using fuzz Partial ratio.mp4 (80.2 MB)
    • 2. String Matching using fuzz Partial ratio.srt (13.6 KB)
    • 3. String Matching using Token Sort ratio.mp4 (65.8 MB)
    • 3. String Matching using Token Sort ratio.srt (11.3 KB)
    • 4. String Matching using Token set ratio..mp4 (52.3 MB)
    • 4. String Matching using Token set ratio..srt (8.5 KB)
    • 5. String Matching using Longest sub-string...mp4 (109.5 MB)
    • 5. String Matching using Longest sub-string...srt (18.8 KB)
    7. Advance Feature Engineering in Data ScienceNLPML
    • 1. Create some set of features like [ first_word , last_word & length_diff ].mp4 (99.5 MB)
    • 1. Create some set of features like [ first_word , last_word & length_diff ].srt (18.7 KB)
    • 2. What are stopwords & how to remove it from data. .mp4 (124.2 MB)
    • 2. What are stopwords & how to remove it from data. .srt (18.6 KB)
    • 3. Finding common_word_count_min & common_word_count_max.mp4 (112.4 MB)
    • 3. Finding common_word_count_min & common_word_count_max.srt (18.4 KB)
    • 4. Lecture 25.mp4 (102.3 MB)
    • 4. Lecture 25.srt (16.7 KB)
    • 5. Lecture 26.mp4 (64.6 MB)
    • 5. Lecture 26.srt (10.2 KB)
    • 6. Lecture 27.mp4 (63.8 MB)
    • 6. Lecture 27.srt (11.3 KB)
    8. Advance Data Analysis
    • 1. Lecture 28.mp4 (109.0 MB)
    • 1. Lecture 28.srt (18.3 KB)
    • 2. Lecture 29.mp4 (78.5 MB)
    • 2. Lecture 29.srt (14.1 KB)
    • 3. Lecture 30.mp4 (108.0 MB)
    • 3. Lecture 30.srt (17.6 KB)
    9. NLP (Natural Language Processing )
    • 1. Lecture 31.mp4 (85.7 MB)
    • 1. Lecture 31.srt (17.7 KB)
    • 2. Lecture 32.mp4 (68.6 MB)
    • 2. Lecture 32.srt (13.8 KB)
    • 3. Lecture 33.mp4 (87.4 MB)
    • 3. Lecture 33.srt (15.3 KB)
    • 4. Lecture 34.mp4 (123.4 MB)
    • 4. Lecture 34.srt (18.0 KB)
    • 5. Lecture 35.mp4 (125.0 MB)
    • 5. Lecture 35.srt (20.9 KB)
    • Bonus Resources.txt (0.4 KB)

Code:

  • udp://tracker.torrent.eu.org:451/announce
  • udp://tracker.tiny-vps.com:6969/announce
  • http://tracker.foreverpirates.co:80/announce
  • udp://tracker.cyberia.is:6969/announce
  • udp://exodus.desync.com:6969/announce
  • udp://explodie.org:6969/announce
  • udp://tracker.opentrackr.org:1337/announce
  • udp://9.rarbg.to:2780/announce
  • udp://tracker.internetwarriors.net:1337/announce
  • udp://ipv4.tracker.harry.lu:80/announce
  • udp://open.stealth.si:80/announce
  • udp://9.rarbg.to:2900/announce
  • udp://9.rarbg.me:2720/announce
  • udp://opentor.org:2710/announce