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Udemy - Machine Learning, Data Science and Deep Learning with Python

Torrent Info
Category Other
Added Friday 2nd June 2023 06:44:42 AM (3 years ago)
Size7.7 GB
Peers1 Peers (0 Seeders and 1 leechers) update
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Torrent Files (220)
FilenameSize
1. Getting Started/1. Introduction.mp459.6 MB
1. Getting Started/1. Introduction.srt4.7 KB
1. Getting Started/10. [Activity] Python Basics, Part 4 [Optional].mp421.1 MB
1. Getting Started/10. [Activity] Python Basics, Part 4 [Optional].srt21.1 MB
1. Getting Started/11. Introducing the Pandas Library [Optional].mp4123.1 MB
1. Getting Started/11. Introducing the Pandas Library [Optional].srt18.0 KB
1. Getting Started/2. Udemy 101 Getting the Most From This Course.mp419.8 MB
1. Getting Started/2. Udemy 101 Getting the Most From This Course.srt4.0 KB
1. Getting Started/3. Installation Getting Started.html265 bytes
1. Getting Started/4. [Activity] WINDOWS Installing and Using Anaconda & Course Materials.mp4102.8 MB
1. Getting Started/4. [Activity] WINDOWS Installing and Using Anaconda & Course Materials.srt18.9 KB
1. Getting Started/5. [Activity] MAC Installing and Using Anaconda & Course Materials.mp496.5 MB
1. Getting Started/5. [Activity] MAC Installing and Using Anaconda & Course Materials.srt14.5 KB
1. Getting Started/6. [Activity] LINUX Installing and Using Anaconda & Course Materials.mp480.2 MB
1. Getting Started/6. [Activity] LINUX Installing and Using Anaconda & Course Materials.srt14.7 KB
1. Getting Started/7. Python Basics, Part 1 [Optional].mp433.0 MB
1. Getting Started/7. Python Basics, Part 1 [Optional].srt7.8 KB
1. Getting Started/8. [Activity] Python Basics, Part 2 [Optional].mp420.6 MB
1. Getting Started/8. [Activity] Python Basics, Part 2 [Optional].srt7.6 KB
1. Getting Started/9. [Activity] Python Basics, Part 3 [Optional].mp410.1 MB
1. Getting Started/9. [Activity] Python Basics, Part 3 [Optional].srt4.2 KB
10. Deep Learning and Neural Networks/1. Deep Learning Pre-Requisites.mp474.2 MB
10. Deep Learning and Neural Networks/1. Deep Learning Pre-Requisites.srt21.5 KB
10. Deep Learning and Neural Networks/10. [Activity] Using Keras to Predict Political Affiliations.mp488.2 MB
10. Deep Learning and Neural Networks/10. [Activity] Using Keras to Predict Political Affiliations.srt21.1 KB
10. Deep Learning and Neural Networks/11. Convolutional Neural Networks (CNN's).mp493.1 MB
10. Deep Learning and Neural Networks/11. Convolutional Neural Networks (CNN's).srt19.9 KB
10. Deep Learning and Neural Networks/12. [Activity] Using CNN's for handwriting recognition.mp469.6 MB
10. Deep Learning and Neural Networks/12. [Activity] Using CNN's for handwriting recognition.srt13.8 KB
10. Deep Learning and Neural Networks/13. Recurrent Neural Networks (RNN's).mp469.2 MB
10. Deep Learning and Neural Networks/13. Recurrent Neural Networks (RNN's).srt18.5 KB
10. Deep Learning and Neural Networks/14. [Activity] Using a RNN for sentiment analysis.mp481.4 MB
10. Deep Learning and Neural Networks/14. [Activity] Using a RNN for sentiment analysis.srt16.8 KB
10. Deep Learning and Neural Networks/15. [Activity] Transfer Learning.mp4115.3 MB
10. Deep Learning and Neural Networks/15. [Activity] Transfer Learning.srt21.5 KB
10. Deep Learning and Neural Networks/16. Tuning Neural Networks Learning Rate and Batch Size Hyperparameters.mp418.4 MB
10. Deep Learning and Neural Networks/16. Tuning Neural Networks Learning Rate and Batch Size Hyperparameters.srt8.3 KB
10. Deep Learning and Neural Networks/17. Deep Learning Regularization with Dropout and Early Stopping.mp433.6 MB
10. Deep Learning and Neural Networks/17. Deep Learning Regularization with Dropout and Early Stopping.srt12.0 KB
10. Deep Learning and Neural Networks/18. The Ethics of Deep Learning.mp4128.2 MB
10. Deep Learning and Neural Networks/18. The Ethics of Deep Learning.srt19.8 KB
10. Deep Learning and Neural Networks/19. Learning More about Deep Learning.mp438.6 MB
10. Deep Learning and Neural Networks/19. Learning More about Deep Learning.srt3.1 KB
10. Deep Learning and Neural Networks/2. The History of Artificial Neural Networks.mp480.0 MB
10. Deep Learning and Neural Networks/2. The History of Artificial Neural Networks.srt19.1 KB
10. Deep Learning and Neural Networks/3. [Activity] Deep Learning in the Tensorflow Playground.mp4141.6 MB
10. Deep Learning and Neural Networks/3. [Activity] Deep Learning in the Tensorflow Playground.srt19.7 KB
10. Deep Learning and Neural Networks/4. Deep Learning Details.mp464.2 MB
10. Deep Learning and Neural Networks/4. Deep Learning Details.srt16.8 KB
10. Deep Learning and Neural Networks/5. Introducing Tensorflow.mp464.2 MB
10. Deep Learning and Neural Networks/5. Introducing Tensorflow.srt20.2 KB
10. Deep Learning and Neural Networks/6. Important note about Tensorflow 2.html644 bytes
10. Deep Learning and Neural Networks/7. [Activity] Using Tensorflow, Part 1.mp4118.2 MB
10. Deep Learning and Neural Networks/7. [Activity] Using Tensorflow, Part 1.srt23.5 KB
10. Deep Learning and Neural Networks/8. [Activity] Using Tensorflow, Part 2.mp4104.5 MB
10. Deep Learning and Neural Networks/8. [Activity] Using Tensorflow, Part 2.srt21.6 KB
10. Deep Learning and Neural Networks/9. [Activity] Introducing Keras.mp492.1 MB
10. Deep Learning and Neural Networks/9. [Activity] Introducing Keras.srt23.7 KB
11. Final Project/1. Your final project assignment.mp451.6 MB
11. Final Project/1. Your final project assignment.srt11.6 KB
11. Final Project/2. Final project review.mp498.5 MB
11. Final Project/2. Final project review.srt24.5 KB
12. You made it!/1. More to Explore.mp464.1 MB
12. You made it!/1. More to Explore.srt7.2 KB
12. You made it!/2. Don't Forget to Leave a Rating!.html564 bytes
12. You made it!/3. Bonus Lecture More courses to explore!.html7.4 KB
2. Statistics and Probability Refresher, and Python Practice/1. Types of Data.mp477.2 MB
2. Statistics and Probability Refresher, and Python Practice/1. Types of Data.srt16.2 KB
2. Statistics and Probability Refresher, and Python Practice/10. [Activity] Covariance and Correlation.mp4116.7 MB
2. Statistics and Probability Refresher, and Python Practice/10. [Activity] Covariance and Correlation.srt25.9 KB
2. Statistics and Probability Refresher, and Python Practice/11. [Exercise] Conditional Probability.mp4125.1 MB
2. Statistics and Probability Refresher, and Python Practice/11. [Exercise] Conditional Probability.srt28.4 KB
2. Statistics and Probability Refresher, and Python Practice/12. Exercise Solution Conditional Probability of Purchase by Age.mp422.0 MB
2. Statistics and Probability Refresher, and Python Practice/12. Exercise Solution Conditional Probability of Purchase by Age.srt4.0 KB
2. Statistics and Probability Refresher, and Python Practice/13. Bayes' Theorem.mp458.9 MB
2. Statistics and Probability Refresher, and Python Practice/13. Bayes' Theorem.srt11.5 KB
2. Statistics and Probability Refresher, and Python Practice/2. Mean, Median, Mode.mp456.1 MB
2. Statistics and Probability Refresher, and Python Practice/2. Mean, Median, Mode.srt13.0 KB
2. Statistics and Probability Refresher, and Python Practice/3. [Activity] Using mean, median, and mode in Python.mp461.9 MB
2. Statistics and Probability Refresher, and Python Practice/3. [Activity] Using mean, median, and mode in Python.srt15.0 KB
2. Statistics and Probability Refresher, and Python Practice/4. [Activity] Variation and Standard Deviation.mp4110.8 MB
2. Statistics and Probability Refresher, and Python Practice/4. [Activity] Variation and Standard Deviation.srt25.8 KB
2. Statistics and Probability Refresher, and Python Practice/5. Probability Density Function; Probability Mass Function.mp430.1 MB
2. Statistics and Probability Refresher, and Python Practice/5. Probability Density Function; Probability Mass Function.srt7.6 KB
2. Statistics and Probability Refresher, and Python Practice/6. Common Data Distributions.mp475.4 MB
2. Statistics and Probability Refresher, and Python Practice/6. Common Data Distributions.srt16.1 KB
2. Statistics and Probability Refresher, and Python Practice/7. [Activity] Percentiles and Moments.mp4114.0 MB
2. Statistics and Probability Refresher, and Python Practice/7. [Activity] Percentiles and Moments.srt28.3 KB
2. Statistics and Probability Refresher, and Python Practice/8. [Activity] A Crash Course in matplotlib.mp4129.3 MB
2. Statistics and Probability Refresher, and Python Practice/8. [Activity] A Crash Course in matplotlib.srt28.6 KB
2. Statistics and Probability Refresher, and Python Practice/9. [Activity] Advanced Visualization with Seaborn.mp4147.8 MB
2. Statistics and Probability Refresher, and Python Practice/9. [Activity] Advanced Visualization with Seaborn.srt30.0 KB
3. Predictive Models/1. [Activity] Linear Regression.mp4100.5 MB
3. Predictive Models/1. [Activity] Linear Regression.srt25.7 KB
3. Predictive Models/2. [Activity] Polynomial Regression.mp466.8 MB
3. Predictive Models/2. [Activity] Polynomial Regression.srt17.6 KB
3. Predictive Models/3. [Activity] Multiple Regression, and Predicting Car Prices.mp473.9 MB
3. Predictive Models/3. [Activity] Multiple Regression, and Predicting Car Prices.srt21.1 KB
3. Predictive Models/4. Multi-Level Models.mp447.5 MB
3. Predictive Models/4. Multi-Level Models.srt10.7 KB
4. Machine Learning with Python/1. Supervised vs. Unsupervised Learning, and TrainTest.mp498.6 MB
4. Machine Learning with Python/1. Supervised vs. Unsupervised Learning, and TrainTest.srt20.9 KB
4. Machine Learning with Python/10. [Activity] LINUX Installing Graphviz.mp47.0 MB
4. Machine Learning with Python/10. [Activity] LINUX Installing Graphviz.srt1.1 KB
4. Machine Learning with Python/11. Decision Trees Concepts.mp486.5 MB
4. Machine Learning with Python/11. Decision Trees Concepts.srt21.1 KB
4. Machine Learning with Python/12. [Activity] Decision Trees Predicting Hiring Decisions.mp495.9 MB
4. Machine Learning with Python/12. [Activity] Decision Trees Predicting Hiring Decisions.srt22.4 KB
4. Machine Learning with Python/13. Ensemble Learning.mp465.2 MB
4. Machine Learning with Python/13. Ensemble Learning.srt14.5 KB
4. Machine Learning with Python/14. Support Vector Machines (SVM) Overview.mp444.7 MB
4. Machine Learning with Python/14. Support Vector Machines (SVM) Overview.srt9.9 KB
4. Machine Learning with Python/15. [Activity] Using SVM to cluster people using scikit-learn.mp446.7 MB
4. Machine Learning with Python/15. [Activity] Using SVM to cluster people using scikit-learn.srt16.7 KB
4. Machine Learning with Python/2. [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.mp458.1 MB
4. Machine Learning with Python/2. [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.srt13.1 KB
4. Machine Learning with Python/3. Bayesian Methods Concepts.mp440.7 MB
4. Machine Learning with Python/3. Bayesian Methods Concepts.srt8.8 KB
4. Machine Learning with Python/4. [Activity] Implementing a Spam Classifier with Naive Bayes.mp489.1 MB
4. Machine Learning with Python/4. [Activity] Implementing a Spam Classifier with Naive Bayes.srt17.4 KB
4. Machine Learning with Python/5. K-Means Clustering.mp471.9 MB
4. Machine Learning with Python/5. K-Means Clustering.srt17.2 KB
4. Machine Learning with Python/6. [Activity] Clustering people based on income and age.mp457.3 MB
4. Machine Learning with Python/6. [Activity] Clustering people based on income and age.srt11.5 KB
4. Machine Learning with Python/7. Measuring Entropy.mp435.0 MB
4. Machine Learning with Python/7. Measuring Entropy.srt6.9 KB
4. Machine Learning with Python/8. [Activity] WINDOWS Installing Graphviz.mp42.1 MB
4. Machine Learning with Python/8. [Activity] WINDOWS Installing Graphviz.srt689 bytes
4. Machine Learning with Python/9. [Activity] MAC Installing Graphviz.mp414.8 MB
4. Machine Learning with Python/9. [Activity] MAC Installing Graphviz.srt1.3 KB
5. Recommender Systems/1. User-Based Collaborative Filtering.mp486.4 MB
5. Recommender Systems/1. User-Based Collaborative Filtering.srt19.4 KB
5. Recommender Systems/2. Item-Based Collaborative Filtering.mp475.0 MB
5. Recommender Systems/2. Item-Based Collaborative Filtering.srt20.0 KB
5. Recommender Systems/3. [Activity] Finding Movie Similarities.mp4107.8 MB
5. Recommender Systems/3. [Activity] Finding Movie Similarities.srt20.1 KB
5. Recommender Systems/4. [Activity] Improving the Results of Movie Similarities.mp494.9 MB
5. Recommender Systems/4. [Activity] Improving the Results of Movie Similarities.srt16.8 KB
5. Recommender Systems/5. [Activity] Making Movie Recommendations to People.mp4132.6 MB
5. Recommender Systems/5. [Activity] Making Movie Recommendations to People.srt22.6 KB
5. Recommender Systems/6. [Exercise] Improve the recommender's results.mp484.2 MB
5. Recommender Systems/6. [Exercise] Improve the recommender's results.srt13.2 KB
6. More Data Mining and Machine Learning Techniques/1. K-Nearest-Neighbors Concepts.mp440.3 MB
6. More Data Mining and Machine Learning Techniques/1. K-Nearest-Neighbors Concepts.srt8.9 KB
6. More Data Mining and Machine Learning Techniques/2. [Activity] Using KNN to predict a rating for a movie.mp4142.1 MB
6. More Data Mining and Machine Learning Techniques/2. [Activity] Using KNN to predict a rating for a movie.srt28.5 KB
6. More Data Mining and Machine Learning Techniques/3. Dimensionality Reduction; Principal Component Analysis.mp467.7 MB
6. More Data Mining and Machine Learning Techniques/3. Dimensionality Reduction; Principal Component Analysis.srt12.3 KB
6. More Data Mining and Machine Learning Techniques/4. [Activity] PCA Example with the Iris data set.mp4109.7 MB
6. More Data Mining and Machine Learning Techniques/4. [Activity] PCA Example with the Iris data set.srt21.2 KB
6. More Data Mining and Machine Learning Techniques/5. Data Warehousing Overview ETL and ELT.mp4103.3 MB
6. More Data Mining and Machine Learning Techniques/5. Data Warehousing Overview ETL and ELT.srt19.7 KB
6. More Data Mining and Machine Learning Techniques/6. Reinforcement Learning.mp4132.3 MB
6. More Data Mining and Machine Learning Techniques/6. Reinforcement Learning.srt28.5 KB
6. More Data Mining and Machine Learning Techniques/6.1 Python Markov Decision Process Toolbox.html119 bytes
6. More Data Mining and Machine Learning Techniques/6.2 Pac-Man Example.html145 bytes
6. More Data Mining and Machine Learning Techniques/6.3 Cat and Mouse Example.html140 bytes
6. More Data Mining and Machine Learning Techniques/7. [Activity] Reinforcement Learning & Q-Learning with Gym.mp478.0 MB
6. More Data Mining and Machine Learning Techniques/7. [Activity] Reinforcement Learning & Q-Learning with Gym.srt22.5 KB
6. More Data Mining and Machine Learning Techniques/8. Understanding a Confusion Matrix.mp414.8 MB
6. More Data Mining and Machine Learning Techniques/8. Understanding a Confusion Matrix.srt9.7 KB
6. More Data Mining and Machine Learning Techniques/9. Measuring Classifiers (Precision, Recall, F1, ROC, AUC).mp425.8 MB
6. More Data Mining and Machine Learning Techniques/9. Measuring Classifiers (Precision, Recall, F1, ROC, AUC).srt10.8 KB
7. Dealing with Real-World Data/1. BiasVariance Tradeoff.mp466.3 MB
7. Dealing with Real-World Data/1. BiasVariance Tradeoff.srt14.4 KB
7. Dealing with Real-World Data/10. Binning, Transforming, Encoding, Scaling, and Shuffling.mp447.9 MB
7. Dealing with Real-World Data/10. Binning, Transforming, Encoding, Scaling, and Shuffling.srt14.2 KB
7. Dealing with Real-World Data/2. [Activity] K-Fold Cross-Validation to avoid overfitting.mp4102.3 MB
7. Dealing with Real-World Data/2. [Activity] K-Fold Cross-Validation to avoid overfitting.srt24.5 KB
7. Dealing with Real-World Data/3. Data Cleaning and Normalization.mp478.7 MB
7. Dealing with Real-World Data/3. Data Cleaning and Normalization.srt17.1 KB
7. Dealing with Real-World Data/4. [Activity] Cleaning web log data.mp4129.4 MB
7. Dealing with Real-World Data/4. [Activity] Cleaning web log data.srt23.8 KB
7. Dealing with Real-World Data/5. Normalizing numerical data.mp438.2 MB
7. Dealing with Real-World Data/5. Normalizing numerical data.srt7.7 KB
7. Dealing with Real-World Data/6. [Activity] Detecting outliers.mp436.3 MB
7. Dealing with Real-World Data/6. [Activity] Detecting outliers.srt11.4 KB
7. Dealing with Real-World Data/7. Feature Engineering and the Curse of Dimensionality.mp441.7 MB
7. Dealing with Real-World Data/7. Feature Engineering and the Curse of Dimensionality.srt38.1 MB
7. Dealing with Real-World Data/8. Imputation Techniques for Missing Data.mp449.0 MB
7. Dealing with Real-World Data/8. Imputation Techniques for Missing Data.srt14.3 KB
7. Dealing with Real-World Data/9. Handling Unbalanced Data Oversampling, Undersampling, and SMOTE.mp436.3 MB
7. Dealing with Real-World Data/9. Handling Unbalanced Data Oversampling, Undersampling, and SMOTE.srt9.9 KB
8. Apache Spark Machine Learning on Big Data/1. Warning about Java 11 and Spark 3!.html602 bytes
8. Apache Spark Machine Learning on Big Data/10. TF IDF.mp468.8 MB
8. Apache Spark Machine Learning on Big Data/10. TF IDF.srt14.0 KB
8. Apache Spark Machine Learning on Big Data/11. [Activity] Searching Wikipedia with Spark.mp4103.0 MB
8. Apache Spark Machine Learning on Big Data/11. [Activity] Searching Wikipedia with Spark.srt12.9 KB
8. Apache Spark Machine Learning on Big Data/12. [Activity] Using the Spark 2.0 DataFrame API for MLLib.mp4105.7 MB
8. Apache Spark Machine Learning on Big Data/12. [Activity] Using the Spark 2.0 DataFrame API for MLLib.srt13.9 KB
8. Apache Spark Machine Learning on Big Data/2. Spark installation notes for MacOS and Linux users.html3.6 KB
8. Apache Spark Machine Learning on Big Data/3. [Activity] Installing Spark - Part 1.mp483.6 MB
8. Apache Spark Machine Learning on Big Data/3. [Activity] Installing Spark - Part 1.srt12.0 KB
8. Apache Spark Machine Learning on Big Data/3.1 winutils.exe.html108 bytes
8. Apache Spark Machine Learning on Big Data/4. [Activity] Installing Spark - Part 2.mp4112.0 MB
8. Apache Spark Machine Learning on Big Data/4. [Activity] Installing Spark - Part 2.srt10.6 KB
8. Apache Spark Machine Learning on Big Data/4.1 winutils.exe.html108 bytes
8. Apache Spark Machine Learning on Big Data/5. Spark Introduction.mp489.9 MB
8. Apache Spark Machine Learning on Big Data/5. Spark Introduction.srt21.2 KB
8. Apache Spark Machine Learning on Big Data/6. Spark and the Resilient Distributed Dataset (RDD).mp498.5 MB
8. Apache Spark Machine Learning on Big Data/6. Spark and the Resilient Distributed Dataset (RDD).srt24.4 KB
8. Apache Spark Machine Learning on Big Data/7. Introducing MLLib.mp454.8 MB
8. Apache Spark Machine Learning on Big Data/7. Introducing MLLib.srt54.8 MB
8. Apache Spark Machine Learning on Big Data/8. Introduction to Decision Trees in Spark.mp4134.0 MB
8. Apache Spark Machine Learning on Big Data/8. Introduction to Decision Trees in Spark.srt28.1 KB
8. Apache Spark Machine Learning on Big Data/9. [Activity] K-Means Clustering in Spark.mp4117.9 MB
8. Apache Spark Machine Learning on Big Data/9. [Activity] K-Means Clustering in Spark.srt17.7 KB
9. Experimental Design ML in the Real World/1. Deploying Models to Real-Time Systems.mp433.0 MB
9. Experimental Design ML in the Real World/1. Deploying Models to Real-Time Systems.srt15.4 KB
9. Experimental Design ML in the Real World/2. AB Testing Concepts.mp497.5 MB
9. Experimental Design ML in the Real World/2. AB Testing Concepts.srt20.2 KB
9. Experimental Design ML in the Real World/3. T-Tests and P-Values.mp464.9 MB
9. Experimental Design ML in the Real World/3. T-Tests and P-Values.srt13.2 KB
9. Experimental Design ML in the Real World/4. [Activity] Hands-on With T-Tests.mp481.6 MB
9. Experimental Design ML in the Real World/4. [Activity] Hands-on With T-Tests.srt13.7 KB
9. Experimental Design ML in the Real World/5. Determining How Long to Run an Experiment.mp434.8 MB
9. Experimental Design ML in the Real World/5. Determining How Long to Run an Experiment.srt8.3 KB
9. Experimental Design ML in the Real World/6. AB Test Gotchas.mp496.1 MB
9. Experimental Design ML in the Real World/6. AB Test Gotchas.srt21.9 KB
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