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Udemy - Python Beyond Basics for Machine Learning, Data Science, AI

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Added 5 years ago by tutsnode in Other
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Udemy - Python Beyond Basics for Machine Learning, Data Science, AI (Size: 5.8 GB)
  1. Artificial Intelligence Introduction.mp4 58.2 MB
  1. Artificial Intelligence Introduction.srt 3.9 KB
  1. Brief Introduction of Python.mp4 34.1 MB
  1. Brief Introduction of Python.srt 1.9 KB
  1. Collection Module.mp4 91.7 MB
  1. Collection Module.srt 11.6 KB
  1. Course Introduction in Animation.mp4 25.6 MB
  1. Course Introduction in Animation.srt 0 B
  1. Matplotlib Library Tutorial 1.mp4 204.3 MB
  1. Matplotlib Library Tutorial 1.srt 30.3 KB
  1. Numpy Library Tutorial 1.mp4 218.1 MB
  1. Numpy Library Tutorial 1.srt 40.1 KB
  1. Pandas Tutorial 1.mp4 52.9 MB
  1. Pandas Tutorial 1.srt 10.2 KB
  1. Plotly Library Tutorial.mp4 318.8 MB
  1. Plotly Library Tutorial.srt 39.9 KB
  1. Python Crash Course.mp4 254.4 MB
  1. Python Crash Course.srt 45.2 KB
  1. Scipy Tutorial.mp4 20 MB
  1. Scipy Tutorial.srt 3.1 KB
  1. Seaborn Library Tutorial 1.mp4 82.1 MB
  1. Seaborn Library Tutorial 1.srt 14.4 KB
  1. Tips to Start Project in Data Science.mp4 67 MB
  1. Tips to Start Project in Data Science.srt 8.1 KB
  1. Training, Testing and Model Evaluation in Machine Learning.mp4 29.9 MB
  1. Training, Testing and Model Evaluation in Machine Learning.srt 8.2 KB
  1.1 .ipybb file and csv files.zip 47.6 KB
  1.1 .ipynb files for Practice of Advance Python.zip 248.9 KB
  1.1 .ipynb files for Practice of Scipy Library.zip 1.4 KB
  1.1 .ipynb files.zip 2.3 KB
  1.1 Plotly.zip 2.4 KB
  1.1 Programs.zip 4.1 KB
  1.1 Support file for Practice.zip 214.1 KB
  10. Case Study with KNN Algorithm.mp4 86.9 MB
  10. Case Study with KNN Algorithm.srt 12 KB
  10. Lambda, Map, Filter and Reduce Function.mp4 62.4 MB
  10. Lambda, Map, Filter and Reduce Function.srt 9.9 KB
  10. Tuple Operations in details.mp4 42.9 MB
  10. Tuple Operations in details.srt 6.7 KB
  10.1 Material.zip 436.3 KB
  11. NLP Tutorial.mp4 36.9 MB
  11. NLP Tutorial.srt 5.9 KB
  11. Python Queue.mp4 31.1 MB
  11. Python Queue.srt 6 KB
  11. Set Operations in details.mp4 26.1 MB
  11. Set Operations in details.srt 4.4 KB
  11.1 Material.zip 1.2 KB
  12. Case Study with Scikit Learn Library.mp4 411.8 MB
  12. Case Study with Scikit Learn Library.srt 60.6 KB
  12. Dictionary Operations in details.mp4 28.5 MB
  12. Dictionary Operations in details.srt 4.5 KB
  12. isinstance, Use of format, Timeit(), round(), Slice and abs().mp4 53.7 MB
  12. isinstance, Use of format, Timeit(), round(), Slice and abs().srt 8.2 KB
  12.1 Material.zip 13.4 KB
  13. Case Study with Scikit Learn Library.mp4 278 MB
  13. Case Study with Scikit Learn Library.srt 42.8 KB
  13. Data Type Conversion.mp4 68.3 MB
  13. Data Type Conversion.srt 11.5 KB
  13. Zip Function.mp4 17.1 MB
  13. Zip Function.srt 3.1 KB
  13.1 Material.zip 25.7 KB
  14. Importance of Indentation.mp4 38 MB
  14. Importance of Indentation.srt 6.5 KB
  14. eval(),exec(),repr() function.mp4 27.5 MB
  14. eval(),exec(),repr() function.srt 5.6 KB
  15. Random Number, Range Function.mp4 53 MB
  15. Random Number, Range Function.srt 8.3 KB
  15. Switch Case.mp4 21.1 MB
  15. Switch Case.srt 3.2 KB
  16. Sequential, Selection & Repetition -for, while, break, continue, if-elif else.mp4 52.4 MB
  16. Sequential, Selection & Repetition -for, while, break, continue, if-elif else.srt 13.6 KB
  16. Ternary Operator.mp4 22.5 MB
  16. Ternary Operator.srt 4.2 KB
  17. Math Library.mp4 25.9 MB
  17. Math Library.srt 5 KB
  17. Object Oriented Programming (OOP).mp4 44.6 MB
  17. Object Oriented Programming (OOP).srt 7.3 KB
  18. Datetime and Calendar Module.mp4 44 MB
  18. Datetime and Calendar Module.srt 6.4 KB
  19. Create, Edit, Write, Read Text File.mp4 22.2 MB
  19. Create, Edit, Write, Read Text File.srt 4.5 KB
  2. AI powered Unmanned Ground Vehicle UGV.mp4 47 MB
  2. AI powered Unmanned Ground Vehicle UGV.srt 2.5 KB
  2. Case Study of Suicides in India 2001-2012.mp4 86.9 MB
  2. Case Study of Suicides in India 2001-2012.srt 10.3 KB
  2. Matplotlib Library Tutorial 2.mp4 55.9 MB
  2. Matplotlib Library Tutorial 2.srt 8.8 KB
  2. Numpy Library Tutorial 2.mp4 79.1 MB
  2. Numpy Library Tutorial 2.srt 13 KB
  2. Pandas Tutorial 2.mp4 22 MB
  2. Pandas Tutorial 2.srt 5.1 KB
  2. Python Regular Expression (RegEx).mp4 30.3 MB
  2. Python Regular Expression (RegEx).srt 5.6 KB
  2. Scipy Official Site.mp4 27 MB
  2. Scipy Official Site.srt 2.9 KB
  2. Seaborn Library Tutorial 2.mp4 113.9 MB
  2. Seaborn Library Tutorial 2.srt 15.6 KB
  2. Set Up Environment Google Colab.mp4 40.6 MB
  2. Set Up Environment Google Colab.srt 8.4 KB
  2. Supervised Learning.mp4 25.8 MB
  2. Supervised Learning.srt 0 B
  2. Why to join this course.mp4 21.6 MB
  2. Why to join this course.srt 1.6 KB
  2.1 Material.zip 1.2 MB
  20. Exception Handling in Python.mp4 47.4 MB
  20. Exception Handling in Python.srt 10 KB
  3. Case Study on Google Review using various different plot using Matplotlib.mp4 58 MB
  3. Case Study on Google Review using various different plot using Matplotlib.srt 6.7 KB
  3. Data Type and Variable, Keywords.mp4 64.6 MB
  3. Data Type and Variable, Keywords.srt 12.1 KB
  3. Introduction of Python and Python Libraries.mp4 62.7 MB
  3. Introduction of Python and Python Libraries.srt 9.9 KB
  3. List Comprehension, Frozensets and Assertion.mp4 67.1 MB
  3. Matplotlib Library Tutorial 3.mp4 42.6 MB
  3. Matplotlib Library Tutorial 3.srt 6.1 KB
  3. Numpy Library Tutorial 3.mp4 108.9 MB
  3. Numpy Library Tutorial 3.srt 17 KB
  3. Pandas Tutorial 3.mp4 29.2 MB
  3. Pandas Tutorial 3.srt 5.3 KB
  3. Seaborn Library Tutorial 3.mp4 42 MB
  3. Seaborn Library Tutorial 3.srt 5 KB
  3. UGV Flow Chart.mp4 119.3 MB
  3. UGV Flow Chart.srt 22.8 KB
  3. Unsupervised Learning.mp4 31.7 MB
  3. Unsupervised Learning.srt 4 KB
  3.1 .ipynb files for Practice of Basic Python.zip 158.2 KB
  3.1 .ipynb files.zip 133.8 KB
  3.1 Material.zip 1.2 MB
  3.1 UGV Flow Chart.pdf 70.6 KB
  4. AI Design Part 1 Unmanned Ground Vehicle Path Finding.mp4 61.5 MB
  4. AI Design Part 1 Unmanned Ground Vehicle Path Finding.srt 16.7 KB
  4. Case Study of Titanic Dataset.mp4 75.2 MB
  4. Case Study of Titanic Dataset.srt 9.5 KB
  4. How to take input.mp4 19.6 MB
  4. How to take input.srt 3.9 KB
  4. Matplotlib Library Tutorial 4.mp4 69.7 MB
  4. Matplotlib Library Tutorial 4.srt 9.6 KB
  4. Meet Trainer for this Course.mp4 12.6 MB
  4. Meet Trainer for this Course.srt 1.3 KB
  4. Numpy Library Tutorial 4.mp4 72.3 MB
  4. Numpy Library Tutorial 4.srt 9.4 KB
  4. Pandas Tutorial 4.mp4 26.6 MB
  4. Pandas Tutorial 4.srt 5.1 KB
  4. Python CSV file Operations.mp4 61.4 MB
  4. Python CSV file Operations.srt 7.8 KB
  4. Reinforcement Learning.mp4 25.2 MB
  4. Reinforcement Learning.srt 2.7 KB
  4.1 Material.zip 27.5 KB
  5. AI Design Part 2 Bellman Equation.mp4 40.8 MB
  5. AI Design Part 2 Bellman Equation.srt 10.7 KB
  5. Case Study with Linear Regression.mp4 51 MB
  5. Case Study with Linear Regression.srt 7.9 KB
  5. Data Science Introduction.mp4 89.6 MB
  5. Data Science Introduction.srt 12.2 KB
  5. Matplotlib Library Tutorial 5.mp4 36.2 MB
  5. Matplotlib Library Tutorial 5.srt 3.9 KB
  5. Numpy Library Tutorial 5.mp4 43.5 MB
  5. Numpy Library Tutorial 5.srt 5.6 KB
  5. Pandas Tutorial 5.mp4 21.3 MB
  5. Pandas Tutorial 5.srt 4.6 KB
  5. Print Statement and How to produce output.mp4 28.8 MB
  5. Print Statement and How to produce output.srt 4.2 KB
  5. User Define Functions and inbuilt Function.mp4 41.3 MB
  5. User Define Functions and inbuilt Function.srt 8.1 KB
  5.1 Material.zip 27.2 KB
  6. AI Design Part 3 Markov Decision Tree.mp4 69.7 MB
  6. AI Design Part 3 Markov Decision Tree.srt 16.3 KB
  6. Case Study with Logistic Regression.mp4 88.2 MB
  6. Case Study with Logistic Regression.srt 14.4 KB
  6. Introduction to List, Tuple, Dictionary, Set.mp4 18.5 MB
  6. Introduction to List, Tuple, Dictionary, Set.srt 3.9 KB
  6. Iterator.mp4 26.9 MB
  6. Iterator.srt 6.3 KB
  6. Numpy Library Tutorial 6.mp4 24.6 MB
  6. Numpy Library Tutorial 6.srt 3.3 KB
  6. Pandas Tutorial 6.mp4 61.1 MB
  6. Pandas Tutorial 6.srt 7.9 KB
  6.1 Material.zip 23.7 KB
  7. AI Design Part 4 Q Learning.mp4 43.6 MB
  7. AI Design Part 4 Q Learning.srt 11.5 KB
  7. Case Study with Support Vector Machines (SVM).mp4 71.4 MB
  7. Case Study with Support Vector Machines (SVM).srt 14.9 KB
  7. Generator and decorators.mp4 62.6 MB
  7. Generator and decorators.srt 11.2 KB
  7. Numpy Library Tutorial 7.mp4 19 MB
  7. Numpy Library Tutorial 7.srt 4.1 KB
  7. Pandas Tutorial 7.mp4 44.8 MB
  7. Pandas Tutorial 7.srt 6 KB
  7. String Operations.mp4 53.3 MB
  7. String Operations.srt 9.5 KB
  7.1 Material.zip 1.4 KB
  8. AI for Part 5 Code for Displaying Path.mp4 40.3 MB
  8. AI for Part 5 Code for Displaying Path.srt 8.5 KB
  8. Case Study with Support Vector Machines (SVM).mp4 60.1 MB
  8. Case Study with Support Vector Machines (SVM).srt 6.7 KB
  8. Global and local Variables in Functions.mp4 19.4 MB
  8. Global and local Variables in Functions.srt 3.6 KB
  8. Numpy Official Site Visit.mp4 25.8 MB
  8. Numpy Official Site Visit.srt 2.9 KB
  8. Operators in details.mp4 51.2 MB
  8. Operators in details.srt 9.5 KB
  8. Pandas Tutorial 8.mp4 24.6 MB
  8. Pandas Tutorial 8.srt 3.8 KB
  8.1 Material.zip 3.9 MB
  9. AI for Part 6 Explanation of Code.mp4 33.1 MB
  9. AI for Part 6 Explanation of Code.srt 4.8 KB
  9. Case Study with K Mean Algorithm.mp4 49.9 MB
  9. Case Study with K Mean Algorithm.srt 8.1 KB
  9. List Operations in details.mp4 63.2 MB
  9. List Operations in details.srt 10.5 KB
  9. Pandas Tutorial 9.mp4 22.9 MB
  9. Pandas Tutorial 9.srt 2.7 KB
  9. Python Logging Module.mp4 19.1 MB
  9. Python Logging Module.srt 3.3 KB
  9.1 Code of UGV using AI.zip 345.5 KB
  9.1 Material.zip 1 MB
  TutsNode.com.txt 102 B
  [TGx]Downloaded from torrentgalaxy.to .txt 614 B
  ▲ 219 total files

Description



Description

Learn the Most demanding language of industry with concept applied to Data Science, Machine Learning and AI

Important topics are covered such as Python Basic Concepts, Advance Concept, Python Crash Course, Python Libraries such as numpy, pandas, matplotlib, seaborn, Data Science Concept with Case Studies , Machine Learning and it’s types, Artificial Intelligence with Case Studies
Who this course is for:

Learner who wants to work as python developers
People interested to learn how to program in python
Learner who wants to start career as Python Developer, Data Science and AI

Requirements

It start with Basics
Only Basic Mathematics Concept
This course is intended for absolute beginners in programming

Last Updated 11/2020

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