October 18, 2020 at 11:06 AM
This post was last modified: October 18, 2020 at 11:07 AM by anrbn2. Edited 2 times in total.

Hey Wssup Y'all been away for a while, but back again with a new course I found, idk why no one posted it yet here.

Anyway the course is:

Pentester Academy - Data Science and Machine Learning for Infosec

Course Contents:

1. Course Introduction

2. Lab Setup and Installation

3. Module 1: Pandas Part 1

4. Module 1: Pandas Part 2

5. Module 1: Pandas Part 3

6. Module 1: Pandas Part 4

7. Module 2: K Nearest Neighbors (KNN) Part 1

8. Module 2: K Nearest Neighbors (KNN) Part 2

9. Module 2: K Nearest Neighbors (KNN) Part 3

10. Module 2: K Nearest Neighbors (KNN) Part 4

11. Module 3: Model Evaluation and Linear Regression Part 1

12. Module 3: Model Evaluation and Linear Regression Part 2

13. Module 3: Model Evaluation and Linear Regression Part 3

14. Module 3: Model Evaluation and Linear Regression Part 4

15. Module 4: Logistic Regression Part 1

16. Module 4: Logistic Regression Part 2

17. Module 4: Logistic Regression Part 3

18. Module 4: Logistic Regression Part 4

19. Module 5: Natural Language Processing Part 1

20. Module 5: Natural Language Processing Part 2

21. Module 5: Natural Language Processing Part 3

22. Module 5: Natural Language Processing Part 4

23. Module 6: Naive Bayes Classification Part 1

24. Module 6: Naive Bayes Classification Part 2

25. Module 6: Naive Bayes Classification Part 3

26. Module 6: Naive Bayes Classification Part 4

27. Module 7: Advanced Scikit Learn Part 1

28. Module 7: Advanced Scikit Learn Part 2

29. Module 8: Decision Trees Part 1

30. Module 8: Decision Trees Part 2

31. Module 8: Decision Trees Part 3

32. Module 9: Ensembling Techniques Part 1

33. Module 9: Ensembling Techniques Part 2

34. Module 9: Ensembling Techniques Part 3

35. Module 9: Ensembling Techniques Part 4

36. Module 10: Dimension Reduction Part 1

37. Module 10: Dimension Reduction Part 2

38. Module 10: Dimension Reduction Part 3

39. Module 11: Clustering Part 1

40. Module 11: Clustering Part 2

41. Module 11: Clustering Part 3

42. Module 12: Stochastic Gradient Descent Part 1

43. Module 12: Stochastic Gradient Descent Part 2

44. Module 12: Stochastic Gradient Descent Part 3

45. Module 13: Neural Networks - Deep Learning Part 1

46. Module 13: Neural Networks - Deep Learning Part 2

47. Module 13: Neural Networks - Deep Learning Part 3

48. Module 14: Recommendations Engine Part 1

49. Module 14: Recommendations Engine Part 2

50. Case Study: Detecting Malicious URLs

Anyway the course is:

Pentester Academy - Data Science and Machine Learning for Infosec

Course Contents:

1. Course Introduction

2. Lab Setup and Installation

3. Module 1: Pandas Part 1

4. Module 1: Pandas Part 2

5. Module 1: Pandas Part 3

6. Module 1: Pandas Part 4

7. Module 2: K Nearest Neighbors (KNN) Part 1

8. Module 2: K Nearest Neighbors (KNN) Part 2

9. Module 2: K Nearest Neighbors (KNN) Part 3

10. Module 2: K Nearest Neighbors (KNN) Part 4

11. Module 3: Model Evaluation and Linear Regression Part 1

12. Module 3: Model Evaluation and Linear Regression Part 2

13. Module 3: Model Evaluation and Linear Regression Part 3

14. Module 3: Model Evaluation and Linear Regression Part 4

15. Module 4: Logistic Regression Part 1

16. Module 4: Logistic Regression Part 2

17. Module 4: Logistic Regression Part 3

18. Module 4: Logistic Regression Part 4

19. Module 5: Natural Language Processing Part 1

20. Module 5: Natural Language Processing Part 2

21. Module 5: Natural Language Processing Part 3

22. Module 5: Natural Language Processing Part 4

23. Module 6: Naive Bayes Classification Part 1

24. Module 6: Naive Bayes Classification Part 2

25. Module 6: Naive Bayes Classification Part 3

26. Module 6: Naive Bayes Classification Part 4

27. Module 7: Advanced Scikit Learn Part 1

28. Module 7: Advanced Scikit Learn Part 2

29. Module 8: Decision Trees Part 1

30. Module 8: Decision Trees Part 2

31. Module 8: Decision Trees Part 3

32. Module 9: Ensembling Techniques Part 1

33. Module 9: Ensembling Techniques Part 2

34. Module 9: Ensembling Techniques Part 3

35. Module 9: Ensembling Techniques Part 4

36. Module 10: Dimension Reduction Part 1

37. Module 10: Dimension Reduction Part 2

38. Module 10: Dimension Reduction Part 3

39. Module 11: Clustering Part 1

40. Module 11: Clustering Part 2

41. Module 11: Clustering Part 3

42. Module 12: Stochastic Gradient Descent Part 1

43. Module 12: Stochastic Gradient Descent Part 2

44. Module 12: Stochastic Gradient Descent Part 3

45. Module 13: Neural Networks - Deep Learning Part 1

46. Module 13: Neural Networks - Deep Learning Part 2

47. Module 13: Neural Networks - Deep Learning Part 3

48. Module 14: Recommendations Engine Part 1

49. Module 14: Recommendations Engine Part 2

50. Case Study: Detecting Malicious URLs