FreeCourseSite com Udemy Machine Learning Data Science and Deep Learning with Python

FreeCourseSite com Udemy Machine Learning Data Science and Deep Learning with Python

Name	[FreeCourseSite.com] Udemy - Machine Learning, Data Science and Deep Learning with Python	DOWNLOAD Copy Link
Total Size	8.2 GB
Total Files	224
Hash	168C35C862EB77BCD4B33D0EF26A0F2B18C687C3

/0. Websites you may like/
[CourseClub.ME].url	0.1 KB
[FCS Forum].url	0.1 KB
[FreeCourseSite.com].url	0.1 KB
/1. Getting Started/
1. Introduction.mp4	62.5 MB
1. Introduction.srt	4.9 KB
10. [Activity] Python Basics, Part 4 [Optional].mp4	22.1 MB
10. [Activity] Python Basics, Part 4 [Optional].srt	6.1 KB
11. Introducing the Pandas Library [Optional].mp4	129.1 MB
11. Introducing the Pandas Library [Optional].srt	18.5 KB
2. Udemy 101 Getting the Most From This Course.mp4	20.7 MB
2. Udemy 101 Getting the Most From This Course.srt	4.1 KB
3. Installation Getting Started.html	1.2 KB
4. [Activity] WINDOWS Installing and Using Anaconda & Course Materials.mp4	106.1 MB
4. [Activity] WINDOWS Installing and Using Anaconda & Course Materials.srt	17.4 KB
5. [Activity] MAC Installing and Using Anaconda & Course Materials.mp4	98.5 MB
5. [Activity] MAC Installing and Using Anaconda & Course Materials.srt	14.5 KB
6. [Activity] LINUX Installing and Using Anaconda & Course Materials.mp4	86.7 MB
6. [Activity] LINUX Installing and Using Anaconda & Course Materials.srt	15.4 KB
7. Python Basics, Part 1 [Optional].mp4	34.6 MB
7. Python Basics, Part 1 [Optional].srt	7.9 KB
8. [Activity] Python Basics, Part 2 [Optional].mp4	21.6 MB
8. [Activity] Python Basics, Part 2 [Optional].srt	7.8 KB
9. [Activity] Python Basics, Part 3 [Optional].mp4	10.6 MB
9. [Activity] Python Basics, Part 3 [Optional].srt	4.3 KB
/10. Deep Learning and Neural Networks/
1. Deep Learning Pre-Requisites.mp4	77.8 MB
1. Deep Learning Pre-Requisites.srt	22.0 KB
10. [Activity] Using Keras to Predict Political Affiliations.mp4	92.5 MB
10. [Activity] Using Keras to Predict Political Affiliations.srt	21.6 KB
11. Convolutional Neural Networks (CNN's).mp4	97.6 MB
11. Convolutional Neural Networks (CNN's).srt	20.3 KB
12. [Activity] Using CNN's for handwriting recognition.mp4	72.9 MB
12. [Activity] Using CNN's for handwriting recognition.srt	14.1 KB
13. Recurrent Neural Networks (RNN's).mp4	72.5 MB
13. Recurrent Neural Networks (RNN's).srt	18.9 KB
14. [Activity] Using a RNN for sentiment analysis.mp4	85.3 MB
14. [Activity] Using a RNN for sentiment analysis.srt	17.2 KB
15. [Activity] Transfer Learning.mp4	120.9 MB
15. [Activity] Transfer Learning.srt	22.0 KB
16. Tuning Neural Networks Learning Rate and Batch Size Hyperparameters.mp4	19.3 MB
16. Tuning Neural Networks Learning Rate and Batch Size Hyperparameters.srt	8.5 KB
17. Deep Learning Regularization with Dropout and Early Stopping.mp4	35.3 MB
17. Deep Learning Regularization with Dropout and Early Stopping.srt	12.3 KB
18. The Ethics of Deep Learning.mp4	134.5 MB
18. The Ethics of Deep Learning.srt	20.3 KB
19. Learning More about Deep Learning.mp4	40.5 MB
19. Learning More about Deep Learning.srt	3.2 KB
2. The History of Artificial Neural Networks.mp4	83.9 MB
2. The History of Artificial Neural Networks.srt	19.5 KB
3. [Activity] Deep Learning in the Tensorflow Playground.mp4	148.5 MB
3. [Activity] Deep Learning in the Tensorflow Playground.srt	20.1 KB
4. Deep Learning Details.mp4	67.3 MB
4. Deep Learning Details.srt	17.2 KB
5. Introducing Tensorflow.mp4	67.3 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	124.0 MB
7. [Activity] Using Tensorflow, Part 1.srt	23.6 KB
8. [Activity] Using Tensorflow, Part 2.mp4	109.6 MB
8. [Activity] Using Tensorflow, Part 2.srt	21.7 KB
9. [Activity] Introducing Keras.mp4	96.5 MB
9. [Activity] Introducing Keras.srt	24.3 KB
/11. Final Project/
1. Your final project assignment Mammogram Classification.mp4	54.1 MB
1. Your final project assignment Mammogram Classification.srt	11.8 KB
2. Final project review.mp4	103.3 MB
2. Final project review.srt	25.1 KB
/12. You made it!/
1. More to Explore.mp4	67.2 MB
1. More to Explore.srt	7.4 KB
2. Don't Forget to Leave a Rating!.html	0.6 KB
3. Bonus Lecture More courses to explore!.html	7.5 KB
/2. Statistics and Probability Refresher, and Python Practice/
1. Types of Data (Numerical, Categorical, Ordinal).mp4	81.0 MB
1. Types of Data (Numerical, Categorical, Ordinal).srt	16.6 KB
10. [Activity] Covariance and Correlation.mp4	122.4 MB
10. [Activity] Covariance and Correlation.srt	26.5 KB
11. [Exercise] Conditional Probability.mp4	131.2 MB
11. [Exercise] Conditional Probability.srt	29.1 KB
12. Exercise Solution Conditional Probability of Purchase by Age.mp4	23.1 MB
12. Exercise Solution Conditional Probability of Purchase by Age.srt	4.1 KB
13. Bayes' Theorem.mp4	61.8 MB
13. Bayes' Theorem.srt	11.8 KB
2. Mean, Median, Mode.mp4	58.9 MB
2. Mean, Median, Mode.srt	13.3 KB
3. [Activity] Using mean, median, and mode in Python.mp4	65.0 MB
3. [Activity] Using mean, median, and mode in Python.srt	15.4 KB
4. [Activity] Variation and Standard Deviation.mp4	116.2 MB
4. [Activity] Variation and Standard Deviation.srt	26.5 KB
5. Probability Density Function; Probability Mass Function.mp4	31.5 MB
5. Probability Density Function; Probability Mass Function.srt	7.8 KB
6. Common Data Distributions (Normal, Binomial, Poisson, etc).mp4	79.0 MB
6. Common Data Distributions (Normal, Binomial, Poisson, etc).srt	16.5 KB
7. [Activity] Percentiles and Moments.mp4	119.6 MB
7. [Activity] Percentiles and Moments.srt	29.0 KB
8. [Activity] A Crash Course in matplotlib.mp4	135.6 MB
8. [Activity] A Crash Course in matplotlib.srt	29.3 KB
9. [Activity] Advanced Visualization with Seaborn.mp4	155.0 MB
9. [Activity] Advanced Visualization with Seaborn.srt	30.7 KB
/3. Predictive Models/
1. [Activity] Linear Regression.mp4	105.3 MB
1. [Activity] Linear Regression.srt	26.3 KB
2. [Activity] Polynomial Regression.mp4	70.0 MB
2. [Activity] Polynomial Regression.srt	18.0 KB
3. [Activity] Multiple Regression, and Predicting Car Prices.mp4	77.4 MB
3. [Activity] Multiple Regression, and Predicting Car Prices.srt	21.6 KB
4. Multi-Level Models.mp4	49.8 MB
4. Multi-Level Models.srt	10.9 KB
/4. Machine Learning with Python/
1. Supervised vs. Unsupervised Learning, and TrainTest.mp4	103.4 MB
1. Supervised vs. Unsupervised Learning, and TrainTest.srt	21.4 KB
10. [Activity] LINUX Installing Graphviz.mp4	7.4 MB
10. [Activity] LINUX Installing Graphviz.srt	1.1 KB
11. Decision Trees Concepts.mp4	90.7 MB
11. Decision Trees Concepts.srt	21.6 KB
12. [Activity] Decision Trees Predicting Hiring Decisions.mp4	100.6 MB
12. [Activity] Decision Trees Predicting Hiring Decisions.srt	23.0 KB
13. Ensemble Learning.mp4	68.4 MB
13. Ensemble Learning.srt	14.9 KB
14. [Activity] XGBoost.mp4	107.0 MB
14. [Activity] XGBoost.srt	27.7 KB
15. Support Vector Machines (SVM) Overview.mp4	46.9 MB
15. Support Vector Machines (SVM) Overview.srt	10.1 KB
16. [Activity] Using SVM to cluster people using scikit-learn.mp4	49.0 MB
16. [Activity] Using SVM to cluster people using scikit-learn.srt	17.0 KB
2. [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.mp4	61.0 MB
2. [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.srt	13.4 KB
3. Bayesian Methods Concepts.mp4	42.7 MB
3. Bayesian Methods Concepts.srt	9.0 KB
4. [Activity] Implementing a Spam Classifier with Naive Bayes.mp4	93.4 MB
4. [Activity] Implementing a Spam Classifier with Naive Bayes.srt	17.8 KB
5. K-Means Clustering.mp4	75.4 MB
5. K-Means Clustering.srt	17.6 KB
6. [Activity] Clustering people based on income and age.mp4	60.1 MB
6. [Activity] Clustering people based on income and age.srt	11.8 KB
7. Measuring Entropy.mp4	36.7 MB
7. Measuring Entropy.srt	7.1 KB
8. [Activity] WINDOWS Installing Graphviz.mp4	2.2 MB
8. [Activity] WINDOWS Installing Graphviz.srt	0.7 KB
9. [Activity] MAC Installing Graphviz.mp4	15.5 MB
9. [Activity] MAC Installing Graphviz.srt	1.3 KB
/5. Recommender Systems/
1. User-Based Collaborative Filtering.mp4	90.6 MB
1. User-Based Collaborative Filtering.srt	19.8 KB
2. Item-Based Collaborative Filtering.mp4	78.6 MB
2. Item-Based Collaborative Filtering.srt	20.5 KB
3. [Activity] Finding Movie Similarities using Cosine Similarity.mp4	113.1 MB
3. [Activity] Finding Movie Similarities using Cosine Similarity.srt	20.6 KB
4. [Activity] Improving the Results of Movie Similarities.mp4	99.5 MB
4. [Activity] Improving the Results of Movie Similarities.srt	17.2 KB
5. [Activity] Making Movie Recommendations with Item-Based Collaborative Filtering.mp4	139.0 MB
5. [Activity] Making Movie Recommendations with Item-Based Collaborative Filtering.srt	23.2 KB
6. [Exercise] Improve the recommender's results.mp4	88.3 MB
6. [Exercise] Improve the recommender's results.srt	13.5 KB
/6. More Data Mining and Machine Learning Techniques/
1. K-Nearest-Neighbors Concepts.mp4	42.2 MB
1. K-Nearest-Neighbors Concepts.srt	9.2 KB
2. [Activity] Using KNN to predict a rating for a movie.mp4	149.0 MB
2. [Activity] Using KNN to predict a rating for a movie.srt	29.2 KB
3. Dimensionality Reduction; Principal Component Analysis (PCA).mp4	71.0 MB
3. Dimensionality Reduction; Principal Component Analysis (PCA).srt	12.6 KB
4. [Activity] PCA Example with the Iris data set.mp4	115.1 MB
4. [Activity] PCA Example with the Iris data set.srt	21.7 KB
5. Data Warehousing Overview ETL and ELT.mp4	108.4 MB
5. Data Warehousing Overview ETL and ELT.srt	20.2 KB
6. Reinforcement Learning.mp4	138.7 MB
6. Reinforcement Learning.srt	29.2 KB
6.1 Pac-Man Example.html	0.1 KB
6.2 Python Markov Decision Process Toolbox.html	0.1 KB
6.3 Cat and Mouse Example.html	0.1 KB
7. [Activity] Reinforcement Learning & Q-Learning with Gym.mp4	81.7 MB
7. [Activity] Reinforcement Learning & Q-Learning with Gym.srt	23.0 KB
8. Understanding a Confusion Matrix.mp4	15.5 MB
8. Understanding a Confusion Matrix.srt	9.9 KB
9. Measuring Classifiers (Precision, Recall, F1, ROC, AUC).mp4	26.3 MB
9. Measuring Classifiers (Precision, Recall, F1, ROC, AUC).srt	10.6 KB
/7. Dealing with Real-World Data/
1. BiasVariance Tradeoff.mp4	69.5 MB
1. BiasVariance Tradeoff.srt	14.7 KB
10. Binning, Transforming, Encoding, Scaling, and Shuffling.mp4	50.2 MB
10. Binning, Transforming, Encoding, Scaling, and Shuffling.srt	14.6 KB
2. [Activity] K-Fold Cross-Validation to avoid overfitting.mp4	79.8 MB
2. [Activity] K-Fold Cross-Validation to avoid overfitting.srt	16.8 KB
3. Data Cleaning and Normalization.mp4	82.6 MB
3. Data Cleaning and Normalization.srt	17.5 KB
4. [Activity] Cleaning web log data.mp4	135.7 MB
4. [Activity] Cleaning web log data.srt	24.4 KB
5. Normalizing numerical data.mp4	40.1 MB
5. Normalizing numerical data.srt	7.8 KB
6. [Activity] Detecting outliers.mp4	38.1 MB
6. [Activity] Detecting outliers.srt	11.7 KB
7. Feature Engineering and the Curse of Dimensionality.mp4	43.7 MB
7. Feature Engineering and the Curse of Dimensionality.srt	12.1 KB
8. Imputation Techniques for Missing Data.mp4	51.4 MB
8. Imputation Techniques for Missing Data.srt	14.7 KB
9. Handling Unbalanced Data Oversampling, Undersampling, and SMOTE.mp4	38.1 MB
9. Handling Unbalanced Data Oversampling, Undersampling, and SMOTE.srt	10.1 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	72.2 MB
10. TF IDF.srt	14.4 KB
11. [Activity] Searching Wikipedia with Spark.mp4	108.0 MB
11. [Activity] Searching Wikipedia with Spark.srt	13.2 KB
12. [Activity] Using the Spark 2.0 DataFrame API for MLLib.mp4	110.8 MB
12. [Activity] Using the Spark 2.0 DataFrame API for MLLib.srt	14.2 KB
2. Spark installation notes for MacOS and Linux users.html	3.7 KB
3. [Activity] Installing Spark - Part 1.mp4	87.7 MB
3. [Activity] Installing Spark - Part 1.srt	12.3 KB
3.1 winutils.exe.html	0.1 KB
4. [Activity] Installing Spark - Part 2.mp4	117.4 MB
4. [Activity] Installing Spark - Part 2.srt	10.8 KB
4.1 winutils.exe.html	0.1 KB
5. Spark Introduction.mp4	94.2 MB
5. Spark Introduction.srt	21.7 KB
6. Spark and the Resilient Distributed Dataset (RDD).mp4	103.3 MB
6. Spark and the Resilient Distributed Dataset (RDD).srt	25.0 KB
7. Introducing MLLib.mp4	57.4 MB
7. Introducing MLLib.srt	11.7 KB
8. Introduction to Decision Trees in Spark.mp4	140.5 MB
8. Introduction to Decision Trees in Spark.srt	28.8 KB
9. [Activity] K-Means Clustering in Spark.mp4	123.6 MB
9. [Activity] K-Means Clustering in Spark.srt	18.2 KB
/9. Experimental Design ML in the Real World/
1. Deploying Models to Real-Time Systems.mp4	34.6 MB
1. Deploying Models to Real-Time Systems.srt	15.8 KB
2. AB Testing Concepts.mp4	102.2 MB
2. AB Testing Concepts.srt	20.7 KB
3. T-Tests and P-Values.mp4	68.1 MB
3. T-Tests and P-Values.srt	13.5 KB
4. [Activity] Hands-on With T-Tests.mp4	85.6 MB
4. [Activity] Hands-on With T-Tests.srt	14.0 KB
5. Determining How Long to Run an Experiment.mp4	36.5 MB
5. Determining How Long to Run an Experiment.srt	8.5 KB
6. AB Test Gotchas.mp4	100.8 MB
6. AB Test Gotchas.srt	22.4 KB
Total files 224