Packt Artificial Intelligence and Machine Learning Fundamentals-XQZT

Another exquisit release
Packt.Artificial.Intelligence.and.Machine.Learning.Fundamentals-XQZT
     Title: Artificial Intelligence and Machine Learning Fundamentals
 Publisher: Packt
  Category: Data
      Size: 1708M
     Files: 9F
      Date: 2021-06-01
  Course #: 9781789953671
 Published: Packt
   Updated: N/A
       URL: https://www.packtpub.com/video/big-data-and-business-intelligence/9781789953671
    Author: Zsolt Nagy
  Duration: 5 hours 40 minutes
 Exer/Code: [X]
Installation:
Unpack that shit, run that shit
Description:
AI has already impacted our lives by finding its way into fields
like finance and medicine. Learn how you can create
artificial intelligence applications in Python, and lay down the
foundation for your own lucrative career in data science.

38M	01.01-course_overview_.mkv
17M	01.02-installation_and_setup_.mkv
12M	01.03-lesson_overview_.mkv
30M	01.04-introduction_to_ai_and_machine_learning.mkv
53M	01.05-how_does_ai_solve_real_world_problems_.mkv
31M	01.06-fields_and_applications_of_artificial_intelligence.mkv
24M	01.07-ai_tools_and_learning_models_.mkv
50M	01.08-the_role_of_python_in_artificial_intelligence_.mkv
24M	01.09-a_brief_introduction_to_the_numpy_library.mkv
43M	01.10-python_for_game_ai_.mkv
51M	01.11-breadth_first_search_and_depth_first_search_.mkv
7.5M	01.12-lesson_summary_.mkv
42M	02.01-lesson_overview.mkv
46M	02.02-heuristics.mkv
37M	02.03-tic-tac-toe_.mkv
29M	02.04-pathfinding_with_the_a__algorithm_.mkv
67M	02.05-introducing_the_a__algorithm_.mkv
35M	02.06-game_ai_with_the_minmax_algorithm_.mkv
30M	02.07-game_ai_with_alpha-beta_pruning.mkv
5.0M	02.08-lesson_summary_.mkv
9.4M	03.01-lesson_overview_.mkv
50M	03.02-linear_regression_with_one_variable_.mkv
50M	03.03-fitting_a_model_on_data_with_scikit-learn.mkv
38M	03.04-linear_regression_with_multiple_variables.mkv
39M	03.05-preparing_data_for_protection.mkv
49M	03.06-polynomial_and_support_vector_regression_.mkv
5.5M	03.07-lesson_summary_.mkv
3.3M	04.01-the_fundamentals_of_classification_part_1.mkv
24M	04.02-the_fundamentals_of_classification_part_2.mkv
44M	04.03-the_k-nearest_neighbor_classifier.mkv
48M	04.04-classification_with_support_vector_machines.mkv
47M	04.05-lesson_summary.mkv
4.5M	05.01-lesson_overview.mkv
49M	05.02-introduction_to_decision_trees.mkv
27M	05.03-entropy.mkv
40M	05.04-gini_impurity.mkv
57M	05.05-precision_and_recall.mkv
32M	05.06-random_forest_classifier.mkv
25M	05.07-random_forest_classification_using_scikit-learn.mkv
5.5M	05.08-lesson_summary.mkv
4.9M	06.01-lesson_overview.mkv
41M	06.02-introduction_to_clustering.mkv
48M	06.03-the_k-means_algorithm.mkv
46M	06.04-mean_shift_algorithm.mkv
5.4M	06.05-lesson_summary.mkv
4.5M	07.01-lesson_overview.mkv
47M	07.02-tensorflow_for_python.mkv
56M	07.03-introduction_to_neural_networks.mkv
52M	07.04-forward_and_backward_propagation.mkv
32M	07.05-training_the_tensorflow_model.mkv
20M	07.06-deep_learning.mkv
11M	07.07-lesson_summary.mkv
27M	9781789953671_Code.zip
1.7G	total