FreeTutorials Us Udemy - data-science-and-machine-learning-with-python-hands-on

1. 01 Getting Started/001 Introduction.mp427.73MB
2. 01 Getting Started/002 [Activity] Getting What You Need.mp49.52MB
3. 01 Getting Started/003 [Activity] Installing Enthought Canopy.mp440.51MB
4. 01 Getting Started/004 Python Basics_ Part 1.mp443.97MB
5. 01 Getting Started/005 [Activity] Python Basics_ Part 2.mp428.46MB
6. 01 Getting Started/006 Running Python Scripts.mp421.57MB
7. 01 Getting Started/007 Introducing the Pandas Library.mp443.34MB
8. 02 Statistics and Probability Refresher_ and Python Practise/008 Types of Data.mp434.11MB
9. 02 Statistics and Probability Refresher_ and Python Practise/009 Mean_ Median_ Mode.mp428.17MB
10. 02 Statistics and Probability Refresher_ and Python Practise/010 [Activity] Using mean_ median_ and mode in Python.mp438.99MB
11. 02 Statistics and Probability Refresher_ and Python Practise/011 [Activity] Variation and Standard Deviation.mp445.62MB
12. 02 Statistics and Probability Refresher_ and Python Practise/012 Probability Density Function; Probability Mass Function.mp412.35MB
13. 02 Statistics and Probability Refresher_ and Python Practise/013 Common Data Distributions.mp427.67MB
14. 02 Statistics and Probability Refresher_ and Python Practise/014 [Activity] Percentiles and Moments.mp442.98MB
15. 02 Statistics and Probability Refresher_ and Python Practise/015 [Activity] A Crash Course in matplotlib.mp449.28MB
16. 02 Statistics and Probability Refresher_ and Python Practise/016 [Activity] Covariance and Correlation.mp449.78MB
17. 02 Statistics and Probability Refresher_ and Python Practise/017 [Exercise] Conditional Probability.mp449.55MB
18. 02 Statistics and Probability Refresher_ and Python Practise/018 Exercise Solution_ Conditional Probability of Purchase by Age.mp414.09MB
19. 02 Statistics and Probability Refresher_ and Python Practise/019 Bayes' Theorem.mp430.13MB
20. 03 Predictive Models/020 [Activity] Linear Regression.mp432.97MB
21. 03 Predictive Models/021 [Activity] Polynomial Regression.mp429.78MB
22. 03 Predictive Models/022 [Activity] Multivariate Regression_ and Predicting Car Prices.mp449.97MB
23. 03 Predictive Models/023 Multi-Level Models.mp423.66MB
24. 04 Machine Learning with Python/024 Supervised vs_ Unsupervised Learning_ and Train_Test.mp447.8MB
25. 04 Machine Learning with Python/025 [Activity] Using Train_Test to Prevent Overfitting a Polynomial Regression.mp422.02MB
26. 04 Machine Learning with Python/026 Bayesian Methods_ Concepts.mp419.41MB
27. 04 Machine Learning with Python/027 [Activity] Implementing a Spam Classifier with Naive Bayes.mp436.48MB
28. 04 Machine Learning with Python/028 K-Means Clustering.mp430.3MB
29. 04 Machine Learning with Python/029 [Activity] Clustering people based on income and age.mp423.98MB
30. 04 Machine Learning with Python/030 Measuring Entropy.mp417.48MB
31. 04 Machine Learning with Python/032 Decision Trees_ Concepts.mp439.72MB
32. 04 Machine Learning with Python/033 [Activity] Decision Trees_ Predicting Hiring Decisions.mp438.23MB
33. 04 Machine Learning with Python/034 Ensemble Learning.mp433.7MB
34. 04 Machine Learning with Python/035 Support Vector Machines (SVM) Overview.mp421.77MB
35. 04 Machine Learning with Python/036 [Activity] Using SVM to cluster people using scikit-learn.mp420.84MB
36. 05 Recommender Systems/037 User-Based Collaborative Filtering.mp436.81MB
37. 05 Recommender Systems/038 Item-Based Collaborative Filtering.mp433.56MB
38. 05 Recommender Systems/039 [Activity] Finding Movie Similarities.mp448.48MB
39. 05 Recommender Systems/040 [Activity] Improving the Results of Movie Similarities.mp443.98MB
40. 05 Recommender Systems/041 [Activity] Making Movie Recommendations to People.mp463.25MB
41. 05 Recommender Systems/042 [Exercise] Improve the recommender's results.mp445.85MB
42. 06 More Data Mining and Machine Learning Techniques/043 K-Nearest-Neighbors_ Concepts.mp419.9MB
43. 06 More Data Mining and Machine Learning Techniques/044 [Activity] Using KNN to predict a rating for a movie.mp459.21MB
44. 06 More Data Mining and Machine Learning Techniques/045 Dimensionality Reduction; Principal Component Analysis.mp435.67MB
45. 06 More Data Mining and Machine Learning Techniques/046 [Activity] PCA Example with the Iris data set.mp453.31MB
46. 06 More Data Mining and Machine Learning Techniques/047 Data Warehousing Overview_ ETL and ELT.mp454.11MB
47. 06 More Data Mining and Machine Learning Techniques/048 Reinforcement Learning.mp463.56MB
48. 07 Dealing with Real-World Data/049 Bias_Variance Tradeoff.mp431.23MB
49. 07 Dealing with Real-World Data/050 [Activity] K-Fold Cross-Validation to avoid overfitting.mp445.87MB
50. 07 Dealing with Real-World Data/051 Data Cleaning and Normalization.mp431.9MB
51. 07 Dealing with Real-World Data/052 [Activity] Cleaning web log data.mp460.16MB
52. 07 Dealing with Real-World Data/053 Normalizing numerical data.mp419.02MB
53. 07 Dealing with Real-World Data/054 [Activity] Detecting outliers.mp439.04MB
54. 08 Apache Spark_ Machine Learning on Big Data/056 [Activity] Installing Spark - Part 1.mp444.24MB
55. 08 Apache Spark_ Machine Learning on Big Data/057 [Activity] Installing Spark - Part 2.mp485.81MB
56. 08 Apache Spark_ Machine Learning on Big Data/058 Spark Introduction.mp432.46MB
57. 08 Apache Spark_ Machine Learning on Big Data/059 Spark and the Resilient Distributed Dataset (RDD).mp436.41MB
58. 08 Apache Spark_ Machine Learning on Big Data/060 Introducing MLLib.mp426.27MB
59. 08 Apache Spark_ Machine Learning on Big Data/061 [Activity] Decision Trees in Spark.mp488.24MB
60. 08 Apache Spark_ Machine Learning on Big Data/062 [Activity] K-Means Clustering in Spark.mp462.85MB
61. 08 Apache Spark_ Machine Learning on Big Data/063 TF _ IDF.mp432.2MB
62. 08 Apache Spark_ Machine Learning on Big Data/064 [Activity] Searching Wikipedia with Spark.mp459.76MB
63. 08 Apache Spark_ Machine Learning on Big Data/065 [Activity] Using the Spark 2_0 DataFrame API for MLLib.mp430.53MB
64. 09 Experimental Design/066 A_B Testing Concepts.mp442.69MB
65. 09 Experimental Design/067 T-Tests and P-Values.mp430.11MB
66. 09 Experimental Design/068 [Activity] Hands-on With T-Tests.mp440.06MB
67. 09 Experimental Design/069 Determining How Long to Run an Experiment.mp416.68MB
68. 09 Experimental Design/070 A_B Test Gotchas.mp443.78MB
69. 10 Deep Learning and Neural Networks/071 Deep Learning Pre-Requisites.mp430.43MB
70. 10 Deep Learning and Neural Networks/072 The History of Artificial Neural Networks.mp422.45MB
71. 10 Deep Learning and Neural Networks/073 [Activity] Deep Learning in the Tensorflow Playground.mp449.01MB
72. 10 Deep Learning and Neural Networks/074 Deep Learning Details.mp418.17MB
73. 10 Deep Learning and Neural Networks/075 Introducing Tensorflow.mp425.44MB
74. 10 Deep Learning and Neural Networks/076 [Activity] Using Tensorflow_ Part 1.mp428.35MB
75. 10 Deep Learning and Neural Networks/077 [Activity] Using Tensorflow_ Part 2.mp434.22MB
76. 10 Deep Learning and Neural Networks/078 [Activity] Introducing Keras.mp433.83MB
77. 10 Deep Learning and Neural Networks/079 [Activity] Using Keras to Predict Political Affiliations.mp427.3MB
78. 10 Deep Learning and Neural Networks/080 Convolutional Neural Networks (CNN's).mp423.99MB
79. 10 Deep Learning and Neural Networks/081 [Activity] Using CNN's for handwriting recognition.mp422.43MB
80. 10 Deep Learning and Neural Networks/082 Recurrent Neural Networks (RNN's).mp421.56MB
81. 10 Deep Learning and Neural Networks/083 [Activity] Using a RNN for sentiment analysis.mp427.71MB
82. 10 Deep Learning and Neural Networks/084 The Ethics of Deep Learning.mp453.66MB
83. 10 Deep Learning and Neural Networks/085 Learning More about Deep Learning.mp426.18MB
84. 11 Final Project/086 Your final project assignment.mp419.61MB
85. 11 Final Project/087 Final project review.mp428.03MB
86. 12 You made it!/088 More to Explore.mp445.14MB
87. 12 You made it!/090 Bonus Lecture_ Discounts on my Spark and MapReduce courses!.mp424.32MB