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[DesireCourse.Net] Udemy - Machine Learning, Data Science and Deep Learning with Python
magnet:?xt=urn:btih:439fbeefd2656465636a7d8a71a106396eee7499&dn=[DesireCourse.Net] Udemy - Machine Learning, Data Science and Deep Learning with Python
磁力链接详情
Hash值:
439fbeefd2656465636a7d8a71a106396eee7499
点击数:
142
文件大小:
9.39 GB
文件数量:
105
创建日期:
2021-9-22 15:12
最后访问:
2024-6-26 11:59
访问标签:
DesireCourse
Net
Udemy
-
Machine
Learning
Data
Science
and
Deep
Learning
with
Python
文件列表详情
1. Getting Started/1. Introduction.mp4 59.61 MB
1. Getting Started/10. [Activity] Python Basics, Part 4 [Optional].mp4 21.13 MB
1. Getting Started/11. Introducing the Pandas Library [Optional].mp4 123.11 MB
1. Getting Started/2. Udemy 101 Getting the Most From This Course.mp4 19.78 MB
1. Getting Started/4. [Activity] WINDOWS Installing and Using Anaconda & Course Materials.mp4 102.77 MB
1. Getting Started/5. [Activity] MAC Installing and Using Anaconda & Course Materials.mp4 96.53 MB
1. Getting Started/6. [Activity] LINUX Installing and Using Anaconda & Course Materials.mp4 80.22 MB
1. Getting Started/7. Python Basics, Part 1 [Optional].mp4 32.98 MB
1. Getting Started/8. [Activity] Python Basics, Part 2 [Optional].mp4 20.63 MB
1. Getting Started/9. [Activity] Python Basics, Part 3 [Optional].mp4 10.08 MB
10. Deep Learning and Neural Networks/1. Deep Learning Pre-Requisites.mp4 74.18 MB
10. Deep Learning and Neural Networks/10. [Activity] Using Keras to Predict Political Affiliations.mp4 88.19 MB
10. Deep Learning and Neural Networks/11. Convolutional Neural Networks (CNN's).mp4 93.09 MB
10. Deep Learning and Neural Networks/12. [Activity] Using CNN's for handwriting recognition.mp4 69.57 MB
10. Deep Learning and Neural Networks/13. Recurrent Neural Networks (RNN's).mp4 69.18 MB
10. Deep Learning and Neural Networks/14. [Activity] Using a RNN for sentiment analysis.mp4 81.37 MB
10. Deep Learning and Neural Networks/15. [Activity] Transfer Learning.mp4 115.27 MB
10. Deep Learning and Neural Networks/16. Tuning Neural Networks Learning Rate and Batch Size Hyperparameters.mp4 18.44 MB
10. Deep Learning and Neural Networks/17. Deep Learning Regularization with Dropout and Early Stopping.mp4 33.64 MB
10. Deep Learning and Neural Networks/18. The Ethics of Deep Learning.mp4 128.25 MB
10. Deep Learning and Neural Networks/19. Learning More about Deep Learning.mp4 38.65 MB
10. Deep Learning and Neural Networks/2. The History of Artificial Neural Networks.mp4 79.99 MB
10. Deep Learning and Neural Networks/3. [Activity] Deep Learning in the Tensorflow Playground.mp4 141.58 MB
10. Deep Learning and Neural Networks/4. Deep Learning Details.mp4 64.22 MB
10. Deep Learning and Neural Networks/5. Introducing Tensorflow.mp4 64.16 MB
10. Deep Learning and Neural Networks/7. [Activity] Using Tensorflow, Part 1.mp4 118.23 MB
10. Deep Learning and Neural Networks/8. [Activity] Using Tensorflow, Part 2.mp4 104.55 MB
10. Deep Learning and Neural Networks/9. [Activity] Introducing Keras.mp4 92.06 MB
11. Final Project/1. Your final project assignment.mp4 51.64 MB
11. Final Project/2. Final project review.mp4 98.51 MB
12. You made it!/1. More to Explore.mp4 104.69 MB
2. Statistics and Probability Refresher, and Python Practice/1. Types of Data.mp4 112.17 MB
2. Statistics and Probability Refresher, and Python Practice/10. [Activity] Covariance and Correlation.mp4 167.41 MB
2. Statistics and Probability Refresher, and Python Practice/11. [Exercise] Conditional Probability.mp4 125.15 MB
2. Statistics and Probability Refresher, and Python Practice/12. Exercise Solution Conditional Probability of Purchase by Age.mp4 22.01 MB
2. Statistics and Probability Refresher, and Python Practice/13. Bayes' Theorem.mp4 86.08 MB
2. Statistics and Probability Refresher, and Python Practice/2. Mean, Median, Mode.mp4 82.7 MB
2. Statistics and Probability Refresher, and Python Practice/3. [Activity] Using mean, median, and mode in Python.mp4 61.93 MB
2. Statistics and Probability Refresher, and Python Practice/4. [Activity] Variation and Standard Deviation.mp4 156.35 MB
2. Statistics and Probability Refresher, and Python Practice/5. Probability Density Function; Probability Mass Function.mp4 42.49 MB
2. Statistics and Probability Refresher, and Python Practice/6. Common Data Distributions.mp4 105.82 MB
2. Statistics and Probability Refresher, and Python Practice/7. [Activity] Percentiles and Moments.mp4 159.62 MB
2. Statistics and Probability Refresher, and Python Practice/8. [Activity] A Crash Course in matplotlib.mp4 182.27 MB
2. Statistics and Probability Refresher, and Python Practice/9. [Activity] Advanced Visualization with Seaborn.mp4 147.82 MB
3. Predictive Models/1. [Activity] Linear Regression.mp4 144.36 MB
3. Predictive Models/2. [Activity] Polynomial Regression.mp4 96.61 MB
3. Predictive Models/3. [Activity] Multiple Regression, and Predicting Car Prices.mp4 73.85 MB
3. Predictive Models/4. Multi-Level Models.mp4 69.52 MB
4. Machine Learning with Python/1. Supervised vs. Unsupervised Learning, and TrainTest.mp4 144.92 MB
4. Machine Learning with Python/10. [Activity] LINUX Installing Graphviz.mp4 7.05 MB
4. Machine Learning with Python/11. Decision Trees Concepts.mp4 125.19 MB
4. Machine Learning with Python/12. [Activity] Decision Trees Predicting Hiring Decisions.mp4 134.38 MB
4. Machine Learning with Python/13. Ensemble Learning.mp4 95.42 MB
4. Machine Learning with Python/14. [Activity] XGBoost.mp4 102.09 MB
4. Machine Learning with Python/15. Support Vector Machines (SVM) Overview.mp4 65.67 MB
4. Machine Learning with Python/16. [Activity] Using SVM to cluster people using scikit-learn.mp4 46.71 MB
4. Machine Learning with Python/2. [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.mp4 82.5 MB
4. Machine Learning with Python/3. Bayesian Methods Concepts.mp4 58.05 MB
4. Machine Learning with Python/4. [Activity] Implementing a Spam Classifier with Naive Bayes.mp4 125.19 MB
4. Machine Learning with Python/5. K-Means Clustering.mp4 104 MB
4. Machine Learning with Python/6. [Activity] Clustering people based on income and age.mp4 82.36 MB
4. Machine Learning with Python/7. Measuring Entropy.mp4 52.08 MB
4. Machine Learning with Python/8. [Activity] WINDOWS Installing Graphviz.mp4 2.07 MB
4. Machine Learning with Python/9. [Activity] MAC Installing Graphviz.mp4 14.84 MB
5. Recommender Systems/1. User-Based Collaborative Filtering.mp4 124.65 MB
5. Recommender Systems/2. Item-Based Collaborative Filtering.mp4 108.57 MB
5. Recommender Systems/3. [Activity] Finding Movie Similarities.mp4 152.01 MB
5. Recommender Systems/4. [Activity] Improving the Results of Movie Similarities.mp4 136.49 MB
5. Recommender Systems/5. [Activity] Making Movie Recommendations to People.mp4 188.51 MB
5. Recommender Systems/6. [Exercise] Improve the recommender's results.mp4 128.73 MB
6. More Data Mining and Machine Learning Techniques/1. K-Nearest-Neighbors Concepts.mp4 59.24 MB
6. More Data Mining and Machine Learning Techniques/2. [Activity] Using KNN to predict a rating for a movie.mp4 200.58 MB
6. More Data Mining and Machine Learning Techniques/3. Dimensionality Reduction; Principal Component Analysis.mp4 98.55 MB
6. More Data Mining and Machine Learning Techniques/4. [Activity] PCA Example with the Iris data set.mp4 155.8 MB
6. More Data Mining and Machine Learning Techniques/5. Data Warehousing Overview ETL and ELT.mp4 150.65 MB
6. More Data Mining and Machine Learning Techniques/6. Reinforcement Learning.mp4 189.7 MB
6. More Data Mining and Machine Learning Techniques/7. [Activity] Reinforcement Learning & Q-Learning with Gym.mp4 77.97 MB
6. More Data Mining and Machine Learning Techniques/8. Understanding a Confusion Matrix.mp4 14.84 MB
6. More Data Mining and Machine Learning Techniques/9. Measuring Classifiers (Precision, Recall, F1, ROC, AUC).mp4 25.12 MB
7. Dealing with Real-World Data/1. BiasVariance Tradeoff.mp4 95.81 MB
7. Dealing with Real-World Data/10. Binning, Transforming, Encoding, Scaling, and Shuffling.mp4 47.91 MB
7. Dealing with Real-World Data/2. [Activity] K-Fold Cross-Validation to avoid overfitting.mp4 76.1 MB
7. Dealing with Real-World Data/3. Data Cleaning and Normalization.mp4 112.36 MB
7. Dealing with Real-World Data/4. [Activity] Cleaning web log data.mp4 190.99 MB
7. Dealing with Real-World Data/5. Normalizing numerical data.mp4 56.9 MB
7. Dealing with Real-World Data/6. [Activity] Detecting outliers.mp4 36.33 MB
7. Dealing with Real-World Data/7. Feature Engineering and the Curse of Dimensionality.mp4 41.72 MB
7. Dealing with Real-World Data/8. Imputation Techniques for Missing Data.mp4 49.03 MB
7. Dealing with Real-World Data/9. Handling Unbalanced Data Oversampling, Undersampling, and SMOTE.mp4 36.35 MB
8. Apache Spark Machine Learning on Big Data/10. TF IDF.mp4 100.04 MB
8. Apache Spark Machine Learning on Big Data/11. [Activity] Searching Wikipedia with Spark.mp4 103 MB
8. Apache Spark Machine Learning on Big Data/12. [Activity] Using the Spark 2.0 DataFrame API for MLLib.mp4 105.68 MB
8. Apache Spark Machine Learning on Big Data/3. [Activity] Installing Spark - Part 1.mp4 83.63 MB
8. Apache Spark Machine Learning on Big Data/4. [Activity] Installing Spark - Part 2.mp4 111.98 MB
8. Apache Spark Machine Learning on Big Data/5. Spark Introduction.mp4 127.54 MB
8. Apache Spark Machine Learning on Big Data/6. Spark and the Resilient Distributed Dataset (RDD).mp4 140.62 MB
8. Apache Spark Machine Learning on Big Data/7. Introducing MLLib.mp4 81.23 MB
8. Apache Spark Machine Learning on Big Data/8. Introduction to Decision Trees in Spark.mp4 134.01 MB
8. Apache Spark Machine Learning on Big Data/9. [Activity] K-Means Clustering in Spark.mp4 117.87 MB
9. Experimental Design ML in the Real World/1. Deploying Models to Real-Time Systems.mp4 33.05 MB
9. Experimental Design ML in the Real World/2. AB Testing Concepts.mp4 141.84 MB
9. Experimental Design ML in the Real World/3. T-Tests and P-Values.mp4 95.66 MB
9. Experimental Design ML in the Real World/4. [Activity] Hands-on With T-Tests.mp4 113.84 MB
9. Experimental Design ML in the Real World/5. Determining How Long to Run an Experiment.mp4 51.33 MB
9. Experimental Design ML in the Real World/6. AB Test Gotchas.mp4 139.78 MB
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