FreeCourseLab com Udemy - Machine Learning Data Science and Deep Learning with Python

1. 1. Getting Started/1. Introduction.mp459.6MB
2. 1. Getting Started/2. Udemy 101 Getting the Most From This Course.mp419.78MB
3. 1. Getting Started/3. [Activity] Getting What You Need.mp428.06MB
4. 1. Getting Started/4. [Activity] Installing Enthought Canopy.mp4109.01MB
5. 1. Getting Started/5. Python Basics, Part 1 [Optional].mp4133.83MB
6. 1. Getting Started/6. [Activity] Python Basics, Part 2 [Optional].mp477.2MB
7. 1. Getting Started/7. Running Python Scripts [Optional].mp444.7MB
8. 1. Getting Started/8. Introducing the Pandas Library [Optional].mp4127.88MB
9. 10. Deep Learning and Neural Networks/1. Deep Learning Pre-Requisites.mp467.87MB
10. 10. Deep Learning and Neural Networks/10. Convolutional Neural Networks (CNN's).mp493.09MB
11. 10. Deep Learning and Neural Networks/11. [Activity] Using CNN's for handwriting recognition.mp480.8MB
12. 10. Deep Learning and Neural Networks/12. Recurrent Neural Networks (RNN's).mp469.17MB
13. 10. Deep Learning and Neural Networks/13. [Activity] Using a RNN for sentiment analysis.mp494.77MB
14. 10. Deep Learning and Neural Networks/14. The Ethics of Deep Learning.mp4128.25MB
15. 10. Deep Learning and Neural Networks/15. Learning More about Deep Learning.mp438.65MB
16. 10. Deep Learning and Neural Networks/2. The History of Artificial Neural Networks.mp479.99MB
17. 10. Deep Learning and Neural Networks/3. [Activity] Deep Learning in the Tensorflow Playground.mp4141.58MB
18. 10. Deep Learning and Neural Networks/4. Deep Learning Details.mp464.22MB
19. 10. Deep Learning and Neural Networks/5. Introducing Tensorflow.mp496.39MB
20. 10. Deep Learning and Neural Networks/6. [Activity] Using Tensorflow, Part 1.mp4102.32MB
21. 10. Deep Learning and Neural Networks/7. [Activity] Using Tensorflow, Part 2.mp4133.62MB
22. 10. Deep Learning and Neural Networks/8. [Activity] Introducing Keras.mp4107.45MB
23. 10. Deep Learning and Neural Networks/9. [Activity] Using Keras to Predict Political Affiliations.mp4104.32MB
24. 11. Final Project/1. Your final project assignment.mp458.9MB
25. 11. Final Project/2. Final project review.mp498.5MB
26. 12. You made it!/1. More to Explore.mp464.07MB
27. 2. Statistics and Probability Refresher, and Python Practise/1. Types of Data.mp477.25MB
28. 2. Statistics and Probability Refresher, and Python Practise/10. [Exercise] Conditional Probability.mp4130.37MB
29. 2. Statistics and Probability Refresher, and Python Practise/11. Exercise Solution Conditional Probability of Purchase by Age.mp428.74MB
30. 2. Statistics and Probability Refresher, and Python Practise/12. Bayes' Theorem.mp458.9MB
31. 2. Statistics and Probability Refresher, and Python Practise/2. Mean, Median, Mode.mp456.15MB
32. 2. Statistics and Probability Refresher, and Python Practise/3. [Activity] Using mean, median, and mode in Python.mp492.74MB
33. 2. Statistics and Probability Refresher, and Python Practise/4. [Activity] Variation and Standard Deviation.mp4110.86MB
34. 2. Statistics and Probability Refresher, and Python Practise/5. Probability Density Function; Probability Mass Function.mp430.07MB
35. 2. Statistics and Probability Refresher, and Python Practise/6. Common Data Distributions.mp475.37MB
36. 2. Statistics and Probability Refresher, and Python Practise/7. [Activity] Percentiles and Moments.mp4114.05MB
37. 2. Statistics and Probability Refresher, and Python Practise/8. [Activity] A Crash Course in matplotlib.mp4129.36MB
38. 2. Statistics and Probability Refresher, and Python Practise/9. [Activity] Covariance and Correlation.mp4116.75MB
39. 3. Predictive Models/1. [Activity] Linear Regression.mp4100.47MB
40. 3. Predictive Models/2. [Activity] Polynomial Regression.mp466.77MB
41. 3. Predictive Models/3. [Activity] Multivariate Regression, and Predicting Car Prices.mp4123.78MB
42. 3. Predictive Models/4. Multi-Level Models.mp447.47MB
43. 4. Machine Learning with Python/1. Supervised vs. Unsupervised Learning, and TrainTest.mp498.62MB
44. 4. Machine Learning with Python/10. [Activity] Decision Trees Predicting Hiring Decisions.mp495.95MB
45. 4. Machine Learning with Python/11. Ensemble Learning.mp465.22MB
46. 4. Machine Learning with Python/12. Support Vector Machines (SVM) Overview.mp444.74MB
47. 4. Machine Learning with Python/13. [Activity] Using SVM to cluster people using scikit-learn.mp454.98MB
48. 4. Machine Learning with Python/2. [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.mp458.14MB
49. 4. Machine Learning with Python/3. Bayesian Methods Concepts.mp440.72MB
50. 4. Machine Learning with Python/4. [Activity] Implementing a Spam Classifier with Naive Bayes.mp489.09MB
51. 4. Machine Learning with Python/5. K-Means Clustering.mp471.95MB
52. 4. Machine Learning with Python/6. [Activity] Clustering people based on income and age.mp457.3MB
53. 4. Machine Learning with Python/7. Measuring Entropy.mp434.98MB
54. 4. Machine Learning with Python/9. Decision Trees Concepts.mp486.53MB
55. 5. Recommender Systems/1. User-Based Collaborative Filtering.mp486.37MB
56. 5. Recommender Systems/2. Item-Based Collaborative Filtering.mp475.01MB
57. 5. Recommender Systems/3. [Activity] Finding Movie Similarities.mp4107.83MB
58. 5. Recommender Systems/4. [Activity] Improving the Results of Movie Similarities.mp494.87MB
59. 5. Recommender Systems/5. [Activity] Making Movie Recommendations to People.mp4132.55MB
60. 5. Recommender Systems/6. [Exercise] Improve the recommender's results.mp484.24MB
61. 6. More Data Mining and Machine Learning Techniques/1. K-Nearest-Neighbors Concepts.mp440.28MB
62. 6. More Data Mining and Machine Learning Techniques/2. [Activity] Using KNN to predict a rating for a movie.mp4142.07MB
63. 6. More Data Mining and Machine Learning Techniques/3. Dimensionality Reduction; Principal Component Analysis.mp467.75MB
64. 6. More Data Mining and Machine Learning Techniques/4. [Activity] PCA Example with the Iris data set.mp4109.73MB
65. 6. More Data Mining and Machine Learning Techniques/5. Data Warehousing Overview ETL and ELT.mp4103.34MB
66. 6. More Data Mining and Machine Learning Techniques/6. Reinforcement Learning.mp4132.27MB
67. 7. Dealing with Real-World Data/1. BiasVariance Tradeoff.mp466.31MB
68. 7. Dealing with Real-World Data/2. [Activity] K-Fold Cross-Validation to avoid overfitting.mp4102.34MB
69. 7. Dealing with Real-World Data/3. Data Cleaning and Normalization.mp478.75MB
70. 7. Dealing with Real-World Data/4. [Activity] Cleaning web log data.mp4129.39MB
71. 7. Dealing with Real-World Data/5. Normalizing numerical data.mp438.21MB
72. 7. Dealing with Real-World Data/6. [Activity] Detecting outliers.mp483.6MB
73. 8. Apache Spark Machine Learning on Big Data/10. TF IDF.mp468.85MB
74. 8. Apache Spark Machine Learning on Big Data/11. [Activity] Searching Wikipedia with Spark.mp4111.51MB
75. 8. Apache Spark Machine Learning on Big Data/12. [Activity] Using the Spark 2.0 DataFrame API for MLLib.mp4113.82MB
76. 8. Apache Spark Machine Learning on Big Data/3. [Activity] Installing Spark - Part 1.mp487.37MB
77. 8. Apache Spark Machine Learning on Big Data/4. [Activity] Installing Spark - Part 2.mp4172.29MB
78. 8. Apache Spark Machine Learning on Big Data/5. Spark Introduction.mp489.87MB
79. 8. Apache Spark Machine Learning on Big Data/6. Spark and the Resilient Distributed Dataset (RDD).mp498.52MB
80. 8. Apache Spark Machine Learning on Big Data/7. Introducing MLLib.mp454.75MB
81. 8. Apache Spark Machine Learning on Big Data/8. [Activity] Decision Trees in Spark.mp4193.25MB
82. 8. Apache Spark Machine Learning on Big Data/9. [Activity] K-Means Clustering in Spark.mp4133.83MB
83. 9. Experimental Design/1. AB Testing Concepts.mp497.48MB
84. 9. Experimental Design/2. T-Tests and P-Values.mp464.91MB
85. 9. Experimental Design/3. [Activity] Hands-on With T-Tests.mp481.62MB
86. 9. Experimental Design/4. Determining How Long to Run an Experiment.mp434.85MB
87. 9. Experimental Design/5. AB Test Gotchas.mp496.1MB