Udemy - Machine Learning, Data Science and Deep Learning with Pyt...

  • Category Other
  • Type Tutorials
  • Language English
  • Total size 7.7 GB
  • Uploaded By LMorningStar
  • Downloads 740
  • Last checked 1 week ago
  • Date uploaded 6 years ago
  • Seeders 8
  • Leechers 11

Infohash : 0AABAF0A4D614C15524F6E0A51897B3E70DF722D



Machine Learning, Data Science and Deep Learning with Python



Complete hands-on machine learning tutorial with data science, Tensorflow, artificial intelligence, and neural networks

What you'll learn:

Build artificial neural networks with Tensorflow and Keras
Classify images, data, and sentiments using deep learning
Make predictions using linear regression, polynomial regression, and multivariate regression
Data Visualization with MatPlotLib and Seaborn
Implement machine learning at massive scale with
Apache Spark's MLLib
Understand reinforcement learning - and how to build a
Pac-Man bot

Created by Sundog Education by Frank Kane, Frank Kane
Last updated 12/2019
English

For More Updated Course Visit: freeallcourse.com

Files:

[FreeAllCourse.Com] Udemy - Machine Learning, Data Science and Deep Learning with Python 1. Getting Started
  • 1. Introduction.mp4 (59.6 MB)
  • 1. Introduction.srt (4.7 KB)
  • 10. [Activity] Python Basics, Part 4 [Optional].mp4 (21.1 MB)
  • 10. [Activity] Python Basics, Part 4 [Optional].srt (21.1 MB)
  • 11. Introducing the Pandas Library [Optional].mp4 (123.1 MB)
  • 11. Introducing the Pandas Library [Optional].srt (18.0 KB)
  • 2. Udemy 101 Getting the Most From This Course.mp4 (19.8 MB)
  • 2. Udemy 101 Getting the Most From This Course.srt (4.0 KB)
  • 3. Installation Getting Started.html (0.3 KB)
  • 4. [Activity] WINDOWS Installing and Using Anaconda & Course Materials.mp4 (102.8 MB)
  • 4. [Activity] WINDOWS Installing and Using Anaconda & Course Materials.srt (18.9 KB)
  • 5. [Activity] MAC Installing and Using Anaconda & Course Materials.mp4 (96.5 MB)
  • 5. [Activity] MAC Installing and Using Anaconda & Course Materials.srt (14.5 KB)
  • 6. [Activity] LINUX Installing and Using Anaconda & Course Materials.mp4 (80.2 MB)
  • 6. [Activity] LINUX Installing and Using Anaconda & Course Materials.srt (14.7 KB)
  • 7. Python Basics, Part 1 [Optional].mp4 (33.0 MB)
  • 7. Python Basics, Part 1 [Optional].srt (7.8 KB)
  • 8. [Activity] Python Basics, Part 2 [Optional].mp4 (20.6 MB)
  • 8. [Activity] Python Basics, Part 2 [Optional].srt (7.6 KB)
  • 9. [Activity] Python Basics, Part 3 [Optional].mp4 (10.1 MB)
  • 9. [Activity] Python Basics, Part 3 [Optional].srt (4.2 KB)
10. Deep Learning and Neural Networks
  • 1. Deep Learning Pre-Requisites.mp4 (74.2 MB)
  • 1. Deep Learning Pre-Requisites.srt (21.5 KB)
  • 10. [Activity] Using Keras to Predict Political Affiliations.mp4 (88.2 MB)
  • 10. [Activity] Using Keras to Predict Political Affiliations.srt (21.1 KB)
  • 11. Convolutional Neural Networks (CNN's).mp4 (93.1 MB)
  • 11. Convolutional Neural Networks (CNN's).srt (19.9 KB)
  • 12. [Activity] Using CNN's for handwriting recognition.mp4 (69.6 MB)
  • 12. [Activity] Using CNN's for handwriting recognition.srt (13.8 KB)
  • 13. Recurrent Neural Networks (RNN's).mp4 (69.2 MB)
  • 13. Recurrent Neural Networks (RNN's).srt (18.5 KB)
  • 14. [Activity] Using a RNN for sentiment analysis.mp4 (81.4 MB)
  • 14. [Activity] Using a RNN for sentiment analysis.srt (16.8 KB)
  • 15. [Activity] Transfer Learning.mp4 (115.3 MB)
  • 15. [Activity] Transfer Learning.srt (21.5 KB)
  • 16. Tuning Neural Networks Learning Rate and Batch Size Hyperparameters.mp4 (18.4 MB)
  • 16. Tuning Neural Networks Learning Rate and Batch Size Hyperparameters.srt (8.3 KB)
  • 17. Deep Learning Regularization with Dropout and Early Stopping.mp4 (33.6 MB)
  • 17. Deep Learning Regularization with Dropout and Early Stopping.srt (12.0 KB)
  • 18. The Ethics of Deep Learning.mp4 (128.2 MB)
  • 18. The Ethics of Deep Learning.srt (19.8 KB)
  • 19. Learning More about Deep Learning.mp4 (38.6 MB)
  • 19. Learning More about Deep Learning.srt (3.1 KB)
  • 2. The History of Artificial Neural Networks.mp4 (80.0 MB)
  • 2. The History of Artificial Neural Networks.srt (19.1 KB)
  • 3. [Activity] Deep Learning in the Tensorflow Playground.mp4 (141.6 MB)
  • 3. [Activity] Deep Learning in the Tensorflow Playground.srt (19.7 KB)
  • 4. Deep Learning Details.mp4 (64.2 MB)
  • 4. Deep Learning Details.srt (16.8 KB)
  • 5. Introducing Tensorflow.mp4 (64.2 MB)
  • 5. Introducing Tensorflow.srt (20.2 KB)
  • 6. Important note about Tensorflow 2.html (0.6 KB)
  • 7. [Activity] Using Tensorflow, Part 1.mp4 (118.2 MB)
  • 7. [Activity] Using Tensorflow, Part 1.srt (23.5 KB)
  • 8. [Activity] Using Tensorflow, Part 2.mp4 (104.5 MB)
  • 8. [Activity] Using Tensorflow, Part 2.srt (21.6 KB)
  • 9. [Activity] Introducing Keras.mp4 (92.1 MB)
  • 9. [Activity] Introducing Keras.srt (23.7 KB)
11. Final Project
  • 1. Your final project assignment.mp4 (51.6 MB)
  • 1. Your final project assignment.srt (11.6 KB)
  • 2. Final project review.mp4 (98.5 MB)
  • 2. Final project review.srt (24.5 KB)
12. You made it!
  • 1. More to Explore.mp4 (64.1 MB)
  • 1. More to Explore.srt (7.2 KB)
  • 2. Don't Forget to Leave a Rating!.html (0.6 KB)
  • 3. Bonus Lecture More courses to explore!.html (7.4 KB)
2. Statistics and Probability Refresher, and Python Practice
  • 1. Types of Data.mp4 (77.2 MB)
  • 1. Types of Data.srt (16.2 KB)
  • 10. [Activity] Covariance and Correlation.mp4 (116.7 MB)
  • 10. [Activity] Covariance and Correlation.srt (25.9 KB)
  • 11. [Exercise] Conditional Probability.mp4 (125.1 MB)
  • 11. [Exercise] Conditional Probability.srt (28.4 KB)
  • 12. Exercise Solution Conditional Probability of Purchase by Age.mp4 (22.0 MB)
  • 12. Exercise Solution Conditional Probability of Purchase by Age.srt (4.0 KB)
  • 13. Bayes' Theorem.mp4 (58.9 MB)
  • 13. Bayes' Theorem.srt (11.5 KB)
  • 2. Mean, Median, Mode.mp4 (56.1 MB)
  • 2. Mean, Median, Mode.srt (13.0 KB)
  • 3. [Activity] Using mean, median, and mode in Python.mp4 (61.9 MB)
  • 3. [Activity] Using mean, median, and mode in Python.srt (15.0 KB)
  • 4. [Activity] Variation and Standard Deviation.mp4 (110.8 MB)
  • 4. [Activity] Variation and Standard Deviation.srt (25.8 KB)
  • 5. Probability Density Function; Probability Mass Function.mp4 (30.1 MB)
  • 5. Probability Density Function; Probability Mass Function.srt (7.6 KB)
  • 6. Common Data Distributions.mp4 (75.4 MB)
  • 6. Common Data Distributions.srt (16.1 KB)
  • 7. [Activity] Percentiles and Moments.mp4 (114.0 MB)
  • 7. [Activity] Percentiles and Moments.srt (28.3 KB)
  • 8. [Activity] A Crash Course in matplotlib.mp4 (129.3 MB)
  • 8. [Activity] A Crash Course in matplotlib.srt (28.6 KB)
  • 9. [Activity] Advanced Visualization with Seaborn.mp4 (147.8 MB)
  • 9. [Activity] Advanced Visualization with Seaborn.srt (30.0 KB)
3. Predictive Models
  • 1. [Activity] Linear Regression.mp4 (100.5 MB)
  • 1. [Activity] Linear Regression.srt (25.7 KB)
  • 2. [Activity] Polynomial Regression.mp4 (66.8 MB)
  • 2. [Activity] Polynomial Regression.srt (17.6 KB)
  • 3. [Activity] Multiple Regression, and Predicting Car Prices.mp4 (73.9 MB)
  • 3. [Activity] Multiple Regression, and Predicting Car Prices.srt (21.1 KB)
  • 4. Multi-Level Models.mp4 (47.5 MB)
  • 4. Multi-Level Models.srt (10.7 KB)
4. Machine Learning with Python
  • 1. Supervised vs. Unsupervised Learning, and TrainTest.mp4 (98.6 MB)
  • 1. Supervised vs. Unsupervised Learning, and TrainTest.srt (20.9 KB)
  • 10. [Activity] LINUX Installing Graphviz.mp4 (7.0 MB)
  • 10. [Activity] LINUX Installing Graphviz.srt (1.1 KB)
  • 11. Decision Trees Concepts.mp4 (86.5 MB)
  • 11. Decision Trees Concepts.srt (21.1 KB)
  • 12. [Activity] Decision Trees Predicting Hiring Decisions.mp4 (95.9 MB)
  • 12. [Activity] Decision Trees Predicting Hiring Decisions.srt (22.4 KB)
  • 13. Ensemble Learning.mp4 (65.2 MB)
  • 13. Ensemble Learning.srt (14.5 KB)
  • 14. Support Vector Machines (SVM) Overview.mp4 (44.7 MB)
  • 14. Support Vector Machines (SVM) Overview.srt (9.9 KB)
  • 15. [Activity] Using SVM to cluster people using scikit-learn.mp4 (46.7 MB)
  • 15. [Activity] Using SVM to cluster people using scikit-learn.srt (16.7 KB)
  • 2. [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.mp4 (58.1 MB)
  • 2. [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.srt (13.1 KB)
  • 3. Bayesian Methods Concepts.mp4 (40.7 MB)
  • 3. Bayesian Methods Concepts.srt (8.8 KB)
  • 4. [Activity] Implementing a Spam Classifier with Naive Bayes.mp4 (89.1 MB)
  • 4. [Activity] Implementing a Spam Classifier with Naive Bayes.srt (17.4 KB)
  • 5. K-Means Clustering.mp4 (71.9 MB)
  • 5. K-Means Clustering.srt (17.2 KB)
  • 6. [Activity] Clustering people based on income and age.mp4 (57.3 MB)
  • 6. [Activity] Clustering people based on income and age.srt (11.5 KB)
  • 7. Measuring Entropy.mp4 (35.0 MB)
  • 7. Measuring Entropy.srt (6.9 KB)
  • 8. [Activity] WINDOWS Installing Graphviz.mp4 (2.1 MB)
  • 8. [Activity] WINDOWS Installing Graphviz.srt (0.7 KB)
  • 9. [Activity] MAC Installing Graphviz.mp4 (14.8 MB)
  • 9. [Activity] MAC Installing Graphviz.srt (1.3 KB)
5. Recommender Systems
  • 1. User-Based Collaborative Filtering.mp4 (86.4 MB)
  • 1. User-Based Collaborative Filtering.srt (19.4 KB)
  • 2. Item-Based Collaborative Filtering.mp4 (75.0 MB)
  • 2. Item-Based Collaborative Filtering.srt (20.0 KB)
  • 3. [Activity] Finding Movie Similarities.mp4 (107.8 MB)
  • 3. [Activity] Finding Movie Similarities.srt (20.1 KB)
  • 4. [Activity] Improving the Results of Movie Similarities.mp4 (94.9 MB)
  • 4. [Activity] Improving the Results of Movie Similarities.srt (16.8 KB)
  • 5. [Activity] Making Movie Recommendations to People.mp4 (132.6 MB)
  • 5. [Activity] Making Movie Recommendations to People.srt (22.6 KB)
  • 6. [Exercise] Improve the recommender's results.mp4 (84.2 MB)
  • 6. [Exercise] Improve the recommender's results.srt (13.2 KB)
6. More Data Mining and Machine Learning Techniques
  • 1. K-Nearest-Neighbors Concepts.mp4 (40.3 MB)
  • 1. K-Nearest-Neighbors Concepts.srt (8.9 KB)
  • 2. [Activity] Using KNN to predict a rating for a movie.mp4 (142.1 MB)
  • 2. [Activity] Using KNN to predict a rating for a movie.srt (28.5 KB)
  • 3. Dimensionality Reduction; Principal Component Analysis.mp4 (67.7 MB)
  • 3. Dimensionality Reduction; Principal Component Analysis.srt (12.3 KB)
  • 4. [Activity] PCA Example with the Iris data set.mp4 (109.7 MB)
  • 4. [Activity] PCA Example with the Iris data set.srt (21.2 KB)
  • 5. Data Warehousing Overview ETL and ELT.mp4 (103.3 MB)
  • 5. Data Warehousing Overview ETL and ELT.srt (19.7 KB)
  • 6. Reinforcement Learning.mp4 (132.3 MB)
  • 6. Reinforcement Learning.srt (28.5 KB)
  • 6.1 Python Markov Decision Process Toolbox.html (0.1 KB)
  • 6.2 Pac-Man Example.html (0.1 KB)
  • 6.3 Cat and Mouse Example.html (0.1 KB)
  • 7. [Activity] Reinforcement Learning & Q-Learning with Gym.mp4 (78.0 MB)
  • 7. [Activity] Reinforcement Learning & Q-Learning with Gym.srt (22.5 KB)
  • 8. Understanding a Confusion Matrix.mp4 (14.8 MB)
  • 8. Understanding a Confusion Matrix.srt (9.7 KB)
  • 9. Measuring Classifiers (Precision, Recall, F1, ROC, AUC).mp4 (25.8 MB)
  • 9. Measuring Classifiers (Precision, Recall, F1, ROC, AUC).srt (10.8 KB)
7. Dealing with Real-World Data
  • 1. BiasVariance Tradeoff.mp4 (66.3 MB)
  • 1. BiasVariance Tradeoff.srt (14.4 KB)
  • 10. Binning, Transforming, Encoding, Scaling, and Shuffling.mp4 (47.9 MB)
  • 10. Binning, Transforming, Encoding, Scaling, and Shuffling.srt (14.2 KB)
  • 2. [Activity] K-Fold Cross-Validation to avoid overfitting.mp4 (102.3 MB)
  • 2. [Activity] K-Fold Cross-Validation to avoid overfitting.srt (24.5 KB)
  • 3. Data Cleaning and Normalization.mp4 (78.7 MB)
  • 3. Data Cleaning and Normalization.srt (17.1 KB)
  • 4. [Activity] Cleaning web log data.mp4 (129.4 MB)
  • 4. [Activity] Cleaning web log data.srt (23.8 KB)
  • 5. Normalizing numerical data.mp4 (38.2 MB)
  • 5. Normalizing numerical data.srt (7.7 KB)
  • 6. [Activity] Detecting outliers.mp4 (36.3 MB)
  • 6. [Activity] Detecting outliers.srt (11.4 KB)
  • 7. Feature Engineering and the Curse of Dimensionality.mp4 (41.7 MB)
  • 7. Feature Engineering and the Curse of Dimensionality.srt (38.1 MB)
  • 8. Imputation Techniques for Missing Data.mp4 (49.0 MB)
  • 8. Imputation Techniques for Missing Data.srt (14.3 KB)
  • 9. Handling Unbalanced Data Oversampling, Undersampling, and SMOTE.mp4 (36.3 MB)
  • 9. Handling Unbalanced Data Oversampling, Undersampling, and SMOTE.srt (9.9 KB)
8. Apache Spark Machine Learning on Big Data
  • 1. Warning about Java 11 and Spark 3!.html (0.6 KB)
  • 10. TF IDF.mp4 (68.8 MB)
  • 10. TF IDF.srt (14.0 KB)
  • 11. [Activity] Searching Wikipedia with Spark.mp4 (103.0 MB)
  • 11. [Activity] Searching Wikipedia with Spark.srt (12.9 KB)
  • 12. [Activity] Using the Spark 2.0 DataFrame API for MLLib.mp4 (105.7 MB)
  • 12. [Activity] Using the Spark 2.0 DataFrame API for MLLib.srt (13.9 KB)
  • 2. Spark installation notes for MacOS and Linux users.html (3.6 KB)
  • 3. [Activity] Installing Spark - Part 1.mp4 (83.6 MB)
  • 3. [Activity] Installing Spark - Part 1.srt (12.0 KB)
  • 3.1 winutils.exe.html (0.1 KB)
  • 4. [Activity] Installing Spark - Part 2.mp4 (112.0 MB)
  • 4. [Activity] Installing Spark - Part 2.srt (10.6 KB)
  • 4.1 winutils.exe.html (0.1 KB)
  • 5. Spark Introduction.mp4 (89.9 MB)
  • 5. Spark Introduction.srt (21.2 KB)
  • 6. Spark and the Resilient Distributed Dataset (RDD).mp4 (98.5 MB)
  • 6. Spark and the Resilient Distributed Dataset (RDD).srt (24.4 KB)
  • 7. Introducing MLLib.mp4 (54.8 MB)
  • 7. Introducing MLLib.srt (54.8 MB)
  • 8. Introduction to Decision Trees in Spark.mp4 (134.0 MB)
  • 8. Introduction to Decision Trees in Spark.srt (28.1 KB)
  • 9. [Activity] K-Means Clustering in Spark.mp4 (117.9 MB)
  • 9. [Activity] K-Means Clustering in Spark.srt (17.7 KB)
9. Experimental Design ML in the Real World
  • 1. Deploying Models to Real-Time Systems.mp4 (33.0 MB)
  • 1. Deploying Models to Real-Time Systems.srt (15.4 KB)
  • 2. AB Testing Concepts.mp4 (97.5 MB)
  • 2. AB Testing Concepts.srt (20.2 KB)
  • 3. T-Tests and P-Values.mp4 (64.9 MB)
  • 3. T-Tests and P-Values.srt (13.2 KB)
  • 4. [Activity] Hands-on With T-Tests.mp4 (81.6 MB)
  • 4. [Activity] Hands-on With T-Tests.srt (13.7 KB)
  • 5. Determining How Long to Run an Experiment.mp4 (34.8 MB)
  • 5. Determining How Long to Run an Experiment.srt (8.3 KB)
  • 6. AB Test Gotchas.mp4 (96.1 MB)
  • 6. AB Test Gotchas.srt (21.9 KB)
  • [FreeAllCourse.Com].URL (0.2 KB)

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