Title	[FreeCourseSite.com] Udemy - The Data Science Course Complete Data Science Bootcamp
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001 1.04.Real-life-example.csv	219.83KB
001 2.13.Practical-example.Descriptive-statistics-lesson.xlsx	146.51KB
001 3.17.Practical-example.Confidence-intervals-lesson.xlsx	1.74MB
001 365-Data-Science-Data-Science-Interview-Questions-Guide.pdf	15.56MB
001 4.10.Hypothesis-testing-section-practical-example.xlsx	51.90KB
001 Absenteeism-data.csv	32.05KB
001 Absenteeism-Exercise-Integration.ipynb	62.35KB
001 absenteeism-module.py	6.62KB
001 Absenteeism-new-data.csv	1.87KB
001 Absenteeism-predictions.csv	2.10KB
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001 Additional-Python-Tools-Lectures.ipynb	13.47KB
001 Additional-Python-Tools-Solutions.ipynb	25.49KB
001 An Introduction to Working with Files in Python_en.srt	7.12KB
001 An Introduction to Working with Files in Python.mp4	12.03MB
001 Applying Traditional Data, Big Data, BI, Traditional Data Science and ML_en.srt	11.06KB
001 A Practical Example What You Will Learn in This Course_en.srt	8.17KB
001 A Practical Example What You Will Learn in This Course.mp4	43.94MB
001 Are You Sure You're All Set.html	513B
001 Arithmetic-Operators-Exercise-Py3.ipynb	2.62KB
001 Arithmetic-Operators-Lecture-Py3.ipynb	3.53KB
001 Arithmetic-Operators-Solution-Py3.ipynb	4.24KB
001 Audiobooks-data.csv	710.77KB
001 Audiobooks-data.csv	710.77KB
001 Basic NN Example (Part 1)_en.srt	5.41KB
001 Basic NN Example (Part 1).mp4	9.34MB
001 Bonus Lecture Next Steps.html	3.10KB
001 Business Case Exploring the Dataset and Identifying Predictors_en.srt	13.33KB
001 Business Case Exploring the Dataset and Identifying Predictors.mp4	51.28MB
001 Business Case Getting Acquainted with the Dataset_en.srt	13.24KB
001 Business Case Getting Acquainted with the Dataset.mp4	60.25MB
001 Common-Naming-Conventions.pdf	643.80KB
001 Comparison Operators_en.srt	3.10KB
001 Comparison Operators.mp4	4.82MB
001 Comparison-Operators-Exercise-Py3.ipynb	1.61KB
001 Comparison-Operators-Lecture-Py3.ipynb	2.53KB
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001 Course-notes-descriptive-statistics.pdf	482.21KB
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001 Course-notes-regression-analysis.pdf	312.18KB
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001 Data Science and Business Buzzwords Why are there so Many_en.srt	8.96KB
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001 Debunking Common Misconceptions_en.srt	6.56KB
001 Debunking Common Misconceptions.mp4	58.81MB
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001 EXERCISE - Age vs Probability.html	367B
001 Exploring the Problem with a Machine Learning Mindset_en.srt	5.79KB
001 Finding the Job - What to Expect and What to Look for_en.srt	5.60KB
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001 Fundamentals of Probability Distributions_en.srt	10.10KB
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001 Game Plan for this Python, SQL, and Tableau Business Exercise_en.srt	6.62KB
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001 Glossary.xlsx	19.97KB
001 How to Install TensorFlow 2.0_en.srt	7.91KB
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001 Introduction_en.srt	1.97KB
001 Introduction.mp4	3.06MB
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001 Introduction to Logistic Regression_en.srt	2.17KB
001 Introduction to Logistic Regression.mp4	5.87MB
001 Introduction to Neural Networks_en.srt	7.48KB
001 Introduction to Neural Networks.mp4	10.49MB
001 Introduction to pandas Series_en.srt	13.06KB
001 Introduction to pandas Series.mp4	22.21MB
001 Introduction to Programming_en.srt	8.71KB
001 Introduction to Programming.mp4	14.76MB
001 Introduction-to-Python-Course-Notes.pdf	2.15MB
001 Introduction-to-Python-Course-Notes.pdf	2.15MB
001 Introduction to Regression Analysis_en.srt	2.78KB
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001 Introduction-to-the-If-Statement-Exercise-Py3.ipynb	1.53KB
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001 Introduction-to-the-If-Statement-Solution-Py3.ipynb	2.19KB
001 K-Means Clustering_en.srt	7.92KB
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001 Lists_en.srt	12.54KB
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001 Lists-Lecture-Py3.ipynb	2.70KB
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001 MNIST The Dataset_en.srt	4.36KB
001 MNIST The Dataset.mp4	4.53MB
001 MNIST What is the MNIST Dataset_en.srt	4.30KB
001 MNIST What is the MNIST Dataset.mp4	4.80MB
001 model	1.01KB
001 Multiple Linear Regression_en.srt	4.13KB
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001 Necessary Programming Languages and Software Used in Data Science_en.srt	9.65KB
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001 READ ME!!!!.html	564B
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001 Stochastic Gradient Descent_en.srt	5.79KB
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001 Summary on What You've Learned_en.srt	6.50KB
001 Summary on What You've Learned.mp4	9.86MB
001 Techniques for Working with Traditional Data_en.srt	13.20KB
001 Techniques for Working with Traditional Data.mp4	107.39MB
001 The Basic Probability Formula_en.srt	10.68KB
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001 The Linear Regression Model_en.srt	10.07KB
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001 The Reason Behind These Disciplines_en.srt	7.77KB
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001 What are Confidence Intervals_en.srt	3.84KB
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001 What are Data, Servers, Clients, Requests, and Responses_en.srt	7.55KB
001 What are Data, Servers, Clients, Requests, and Responses.mp4	19.51MB
001 What is a Layer_en.srt	3.18KB
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001 What is a Matrix_en.srt	5.54KB
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001 What is Initialization_en.srt	4.47KB
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001 What is Overfitting_en.srt	6.98KB
001 What is Overfitting.mp4	10.81MB
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001 What is sklearn and How is it Different from Other Packages.encrypted.mp4.part.frag.urls	24.24KB
001 What to Expect from the Following Sections.html	2.43KB
001 What to Expect from this Part_en.srt	5.79KB
001 What to Expect from this Part.mp4	11.73MB
001 Working-with-Text-Files-Lectures.ipynb	27.58KB
002 1.02.Multiple-linear-regression.csv	1.09KB
002 1.04.Real-life-example.csv	219.83KB
002 2.01.Admittance.csv	1.58KB
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002 2.13.Practical-example.Descriptive-statistics-exercise-solution.xlsx	146.38KB
002 3.01.Country-clusters.csv	200B
002 3.17.Practical-example.Confidence-intervals-exercise.xlsx	1.73MB
002 3.17.Practical-example.Confidence-intervals-exercise-solution.xlsx	1.82MB
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002 3.9.Population-variance-known-z-score-lesson.xlsx	11.21KB
002 3.9.The-z-table.xlsx	25.58KB
002 4.10.Hypothesis-testing-section-practical-example-exercise.xlsx	43.69KB
002 4.10.Hypothesis-testing-section-practical-example-exercise-solution.xlsx	44.27KB
002 Absenteeism-predictions.csv	2.10KB
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002 Admittance.ipynb	3.54KB
002 Admittance-with-comments.ipynb	5.32KB
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002 Analyzing Age vs Probability in Tableau.mp4	38.66MB
002 A Simple Example in Python_en.srt	7.07KB
002 A Simple Example in Python.mp4	21.89MB
002 A Simple Example of Clustering_en.srt	11.83KB
002 A Simple Example of Clustering.mp4	34.21MB
002 Basic NN Example (Part 2)_en.srt	8.01KB
002 Basic NN Example (Part 2).mp4	15.23MB
002 Business Case Outlining the Solution_en.srt	2.26KB
002 Business Case Outlining the Solution_en.srt	3.13KB
002 Business Case Outlining the Solution.mp4	3.05MB
002 Business Case Outlining the Solution.mp4	4.16MB
002 Computing Expected Values_en.srt	8.33KB
002 Computing Expected Values.mp4	45.67MB
002 Confidence Intervals; Population Variance Known; Z-score_en.srt	11.59KB
002 Confidence Intervals; Population Variance Known; Z-score.mp4	52.16MB
002 Correlation vs Regression_en.srt	2.60KB
002 Correlation vs Regression.mp4	3.84MB
002 Country-clusters.ipynb	3.31KB
002 Country-clusters-with-comments.ipynb	5.80KB
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002 Creating-a-Function-with-a-Parameter-Lecture-Py3.ipynb	1.59KB
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002 Creating the Targets for the Logistic Regression_en.srt	10.44KB
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002 Deploying the 'absenteeism_module' - Part I_en.srt	5.95KB
002 Deploying the 'absenteeism_module' - Part I.mp4	19.64MB
002 File vs File Object, Reading vs Parsing Data_en.srt	5.06KB
002 File vs File Object, Reading vs Parsing Data.mp4	9.42MB
002 Further Reading on Null and Alternative Hypothesis.html	2.23KB
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002 Help-Yourself-with-Methods-Solution-Py3.ipynb	2.83KB
002 How are we Going to Approach this Section_en.srt	3.61KB
002 How are we Going to Approach this Section.mp4	5.29MB
002 How to Create a Function with a Parameter_en.srt	5.44KB
002 How to Create a Function with a Parameter.mp4	8.33MB
002 How to Install TensorFlow 1_en.srt	4.06KB
002 How to Install TensorFlow 1.mp4	5.00MB
002 Importing the Absenteeism Data in Python_en.srt	4.84KB
002 Importing the Absenteeism Data in Python.mp4	19.53MB
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002 MNIST How to Tackle the MNIST_en.srt	4.34KB
002 MNIST How to Tackle the MNIST_en.srt	4.62KB
002 MNIST How to Tackle the MNIST.mp4	7.95MB
002 MNIST How to Tackle the MNIST.mp4	6.49MB
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002 Practical Example Hypothesis Testing Exercise.html	81B
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002 Problems with Gradient Descent_en.srt	3.56KB
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002 TensorFlow Outline and Comparison with Other Libraries_en.srt	6.56KB
002 TensorFlow Outline and Comparison with Other Libraries.mp4	15.28MB
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002 Ways Sets Can Interact_en.srt	5.48KB
002 Ways Sets Can Interact.mp4	19.30MB
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002 What are Data Connectivity, APIs, and Endpoints_en.srt	10.98KB
002 What are Data Connectivity, APIs, and Endpoints.mp4	60.23MB
002 What Does the Course Cover_en.srt	6.51KB
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002 What is a Deep Net_en.srt	3.87KB
002 What is a Deep Net.mp4	9.12MB
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003 3.9.Population-variance-known-z-score-exercise.xlsx	10.83KB
003 3.9.Population-variance-known-z-score-exercise-solution.xlsx	11.16KB
003 3.9.The-z-table.xlsx	25.58KB
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003 A Note on Installing Packages in Anaconda.html	2.28KB
003 A Note on Multicollinearity.html	849B
003 Another-Way-to-Define-a-Function-Exercise-Py3.ipynb	1.24KB
003 Another-Way-to-Define-a-Function-Lecture-Py3.ipynb	3.29KB
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003 A-Simple-Example-of-Clustering-Solution.ipynb	4.65KB
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003 Basic NN Example (Part 3).mp4	15.65MB
003 Business Analytics, Data Analytics, and Data Science An Introduction_en.srt	13.32KB
003 Business Analytics, Data Analytics, and Data Science An Introduction.mp4	52.62MB
003 Business Case Balancing the Dataset_en.srt	5.15KB
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003 Categorical Variables - Visualization Techniques_en.srt	8.00KB
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003 Characteristics of Discrete Distributions_en.srt	3.04KB
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003 Confidence Intervals; Population Variance Known; Z-score; Exercise.html	81B
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003 Country-clusters-standardized.csv	244B
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003 DeepMind and Deep Learning.html	1.04KB
003 Defining a Function in Python - Part II_en.srt	3.68KB
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003 Deploying the 'absenteeism_module' - Part II_en.srt	9.66KB
003 Deploying the 'absenteeism_module' - Part II.mp4	45.15MB
003 Difference between Classification and Clustering_en.srt	4.36KB
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006 real-estate-price-size.csv	1.86KB
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011 Logistic-Regression-prior-to-Backward-Elimination.url	189B
011 Market-segmentation-example.ipynb	3.80KB
011 Market-segmentation-example-with-comments.ipynb	5.90KB
011 Market Segmentation with Cluster Analysis (Part 1)_en.srt	9.06KB
011 Market Segmentation with Cluster Analysis (Part 1).mp4	28.09MB
011 Mean, median and mode_en.srt	7.18KB
011 Mean, median and mode.mp4	24.49MB
011 MNIST - Exercises.html	1.98KB
011 MNIST Solutions.html	2.22KB
011 Obtaining Dummies from a Single Feature_en.srt	12.67KB
011 Obtaining Dummies from a Single Feature.mp4	69.76MB
011 Optimization Algorithm 1-Parameter Gradient Descent_en.srt	10.58KB
011 Optimization Algorithm 1-Parameter Gradient Descent.mp4	23.59MB
011 pandas DataFrames - Indexing with .iloc[]_en.srt	10.02KB
011 pandas DataFrames - Indexing with .iloc[].mp4	32.22MB
011 Real Life Examples of Machine Learning (ML)_en.srt	3.60KB
011 Real Life Examples of Machine Learning (ML).mp4	27.70MB
011 R-Squared_en.srt	8.12KB
011 R-Squared.mp4	11.20MB
011 sklearn-How-to-properly-include-p-values.ipynb	12.71KB
011 TensorFlow-Audiobooks-Machine-learning-Homework.ipynb	14.40KB
011 TensorFlow-Audiobooks-Machine-Learning-with-comments.ipynb	11.95KB
011 TensorFlow-Audiobooks-Preprocessing-with-comments.ipynb	11.19KB
011 TensorFlow-MNIST-All-Exercises.ipynb	16.65KB
011 TensorFlow-MNIST-around-98-percent-accuracy.ipynb	15.02KB
011 TensorFlow-MNIST-around-98-percent-accuracy.ipynb	17.66KB
011 Test for the Mean. Dependent Samples Exercise.html	81B
011 Why is Linear Algebra Useful_en.srt	13.84KB
011 Why is Linear Algebra Useful.mp4	88.42MB
012 1.02.Multiple-linear-regression.csv	1.07KB
012 2.7.Mean-median-and-mode-exercise.xlsx	10.87KB
012 2.7.Mean-median-and-mode-exercise-solution.xlsx	11.35KB
012 3.14.Confidence-intervals.Two-means.Independent-samples-Part-1-exercise.xlsx	9.83KB
012 3.14.Confidence-intervals.Two-means.Independent-samples-Part-1-exercise-solution.xlsx	10.12KB
012 4.8.Test-for-the-mean.Independent-samples-Part-1-lesson.xlsx	9.63KB
012 Accuracy.ipynb	3.63KB
012 Accuracy-with-comments.ipynb	11.67KB
012 A Practical Example of Bayesian Inference_en.srt	24.29KB
012 A Practical Example of Bayesian Inference.mp4	139.14MB
012 Audiobooks-data.csv	710.77KB
012 Bayesian-Homework.pdf	27.26KB
012 Bayesian-Homework-Solutions.pdf	30.35KB
012 Business Case Final Exercise.html	433B
012 Business Case Final Exercise.html	441B
012 Calculating the Accuracy of the Model_en.srt	5.12KB
012 Calculating the Accuracy of the Model.mp4	20.27MB
012 CDS-2017-2018-Hamilton.pdf	845.31KB
012 Confidence intervals. Two means. Independent Samples (Part 1). Exercise.html	81B
012 Continuous Distributions The Chi-Squared Distribution_en.srt	3.54KB
012 Continuous Distributions The Chi-Squared Distribution.mp4	20.97MB
012 Creating a Summary Table with P-values_en.srt	3.67KB
012 Creating a Summary Table with P-values.mp4	6.45MB
012 Dealing with Categorical Data - Dummy Variables.html	76B
012 EXERCISE - Obtaining Dummies from a Single Feature.html	123B
012 Importing .csv Files - Part II_en.srt	4.56KB
012 Importing .csv Files - Part II.mp4	10.92MB
012 Lending-company.csv	112.43KB
012 Location.csv	13.49KB
012 Market-segmentation-example-Part2.ipynb	4.68KB
012 Market-segmentation-example-Part2-with-comments.ipynb	6.81KB
012 Market Segmentation with Cluster Analysis (Part 2)_en.srt	10.97KB
012 Market Segmentation with Cluster Analysis (Part 2).mp4	34.09MB
012 Mean, Median and Mode Exercise.html	81B
012 MNIST Testing the Model_en.srt	7.14KB
012 MNIST Testing the Model.mp4	22.61MB
012 Multiple-Linear-Regression-with-Dummies-Exercise.ipynb	3.01KB
012 Multiple-Linear-Regression-with-Dummies-Exercise-Solution.ipynb	18.00KB
012 Optimization Algorithm n-Parameter Gradient Descent_en.srt	9.31KB
012 Optimization Algorithm n-Parameter Gradient Descent.mp4	16.83MB
012 pandas DataFrames - Indexing with .loc[]_en.srt	6.68KB
012 pandas DataFrames - Indexing with .loc[].mp4	20.69MB
012 pandas-Fundamentals-Exercises.ipynb	30.96KB
012 pandas-Fundamentals-Lectures.ipynb	21.31KB
012 pandas-Fundamentals-Solutions.ipynb	118.35KB
012 real-estate-price-size-year-view.csv	3.39KB
012 Region.csv	10.22KB
012 Sales-products.csv	152.28KB
012 sklearn-Multiple-Linear-Regression-Summary-Table.ipynb	13.71KB
012 sklearn-Multiple-Linear-Regression-Summary-Table-with-comments.ipynb	16.63KB
012 TensorFlow-Audiobooks-Machine-learning-Homework.ipynb	14.40KB
012 TensorFlow-Audiobooks-Machine-Learning-with-comments.ipynb	11.95KB
012 TensorFlow-Audiobooks-Preprocessing-with-comments.ipynb	11.19KB
012 TensorFlow-MNIST-complete.ipynb	6.78KB
012 TensorFlow-MNIST-complete-with-comments.ipynb	14.51KB
012 Test for the mean. Independent Samples (Part 1)_en.srt	6.54KB
012 Test for the mean. Independent Samples (Part 1).mp4	15.41MB
012 Testing the Model We Created_en.srt	7.81KB
012 Testing the Model We Created.mp4	31.60MB
013 2.8.Skewness-lesson.xlsx	34.63KB
013 3.15.Confidence-intervals.Two-means.Independent-samples-Part-2-lesson.xlsx	9.52KB
013 4.8.Test-for-the-mean.Independent-samples-Part-1-exercise.xlsx	10.77KB
013 4.8.Test-for-the-mean.Independent-samples-Part-1-exercise-solution.xlsx	11.25KB
013 Bank-data.csv	19.55KB
013 Calculating the Accuracy of the Model.html	87B
013 Calculating-the-Accuracy-of-the-Model-Exercise.ipynb	5.39KB
013 Calculating-the-Accuracy-of-the-Model-Solution.ipynb	81.21KB
013 Confidence intervals. Two means. Independent Samples (Part 2)_en.srt	5.60KB
013 Confidence intervals. Two means. Independent Samples (Part 2).mp4	14.62MB
013 Continuous Distributions The Exponential Distribution_en.srt	5.35KB
013 Continuous Distributions The Exponential Distribution.mp4	16.00MB
013 How is Clustering Useful_en.srt	8.08KB
013 How is Clustering Useful.mp4	37.48MB
013 Importing .csv Files - Part III_en.srt	11.12KB
013 Importing .csv Files - Part III.mp4	75.01MB
013 Making-predictions.ipynb	5.77KB
013 Making-predictions-with-comments.ipynb	9.41KB
013 Making Predictions with the Linear Regression_en.srt	5.32KB
013 Making Predictions with the Linear Regression.encrypted.m4a.part	0B
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013 Making Predictions with the Linear Regression.encrypted.mp4.part	0B
013 Making Predictions with the Linear Regression.encrypted.mp4.part.frag.urls	35.91KB
013 Multiple Linear Regression - Exercise.html	76B
013 real-estate-price-size-year.csv	2.35KB
013 Saving the Model and Preparing it for Deployment_en.srt	6.89KB
013 Skewness_en.srt	4.43KB
013 Skewness.mp4	13.31MB
013 sklearn-Multiple-Linear-Regression-Exercise.ipynb	5.67KB
013 sklearn-Multiple-Linear-Regression-Exercise-Solution.ipynb	15.44KB
013 SOLUTION - Obtaining Dummies from a Single Feature.html	117B
013 Test for the mean. Independent Samples (Part 1). Exercise.html	81B
014 1.02.Multiple-linear-regression.csv	1.07KB
014 2.8.Skewness-exercise.xlsx	9.49KB
014 2.8.Skewness-exercise-solution.xlsx	19.78KB
014 3.15.Confidence-intervals.Two-means.Independent-samples-Part-2-exercise.xlsx	9.17KB
014 3.15.Confidence-intervals.Two-means.Independent-samples-Part-2-exercise-solution.xlsx	9.79KB
014 4.9.Test-for-the-mean.Independent-samples-Part-2-lesson.xlsx	9.31KB
014 ARTICLE - A Note on 'pickling'.html	2.11KB
014 Confidence intervals. Two means. Independent Samples (Part 2). Exercise.html	81B
014 Continuous Distributions The Logistic Distribution_en.srt	6.45KB
014 Continuous Distributions The Logistic Distribution.mp4	16.17MB
014 Dropping a Dummy Variable from the Data Set.html	2.31KB
014 EXERCISE Species Segmentation with Cluster Analysis (Part 1).html	87B
014 Feature Scaling (Standardization)_en.srt	11.03KB
014 Feature Scaling (Standardization).mp4	20.36MB
014 Importing Data with index_col_en.srt	4.82KB
014 Importing Data with index_col.mp4	11.63MB
014 iris-dataset.csv	2.40KB
014 Skewness Exercise.html	81B
014 SKLEAR-1.IPY	12.87KB
014 sklearn-Feature-Selection-through-Feature-Scaling-Standardization-Part-1.ipynb	11.73KB
014 Species-Segmentation-with-Cluster-Analysis-Part-1-Exercise.ipynb	4.46KB
014 Species-Segmentation-with-Cluster-Analysis-Part-1-Solution.ipynb	7.35KB
014 Test for the mean. Independent Samples (Part 2)_en.srt	6.46KB
014 Test for the mean. Independent Samples (Part 2).mp4	24.45MB
014 Underfitting and Overfitting_en.srt	6.17KB
014 Underfitting and Overfitting.mp4	7.49MB
015 1.02.Multiple-linear-regression.csv	1.07KB
015 2.03.Test-dataset.csv	322B
015 2.9.Variance-lesson.xlsx	10.08KB
015 4.9.Test-for-the-mean.Independent-samples-Part-2-exercise-2.xlsx	10.54KB
015 4.9.Test-for-the-mean.Independent-samples-Part-2-exercise-2-solution.xlsx	11.39KB
015 A Practical Example of Probability Distributions_en.srt	25.51KB
015 A Practical Example of Probability Distributions.mp4	138.12MB
015 Confidence intervals. Two means. Independent Samples (Part 3)_en.srt	2.42KB
015 Confidence intervals. Two means. Independent Samples (Part 3).mp4	6.89MB
015 Customers-Membership.xlsx	9.69KB
015 Customers-Membership-post.xlsx	15.62KB
015 Daily-Views.xlsx	9.53KB
015 Daily-Views-post.xlsx	20.21KB
015 EXERCISE - Saving the Model (and Scaler).html	284B
015 EXERCISE Species Segmentation with Cluster Analysis (Part 2).html	87B
015 Feature Selection through Standardization of Weights_en.srt	9.25KB
015 Feature Selection through Standardization of Weights.mp4	24.46MB
015 FIFA19.csv	8.64MB
015 FIFA19-post.csv	8.64MB
015 Importing Data with .loadtxt() and .genfromtxt()_en.srt	17.76KB
015 Importing Data with .loadtxt() and .genfromtxt().mp4	56.33MB
015 Importing-Text-Data-with-NumPy-Complete.ipynb	11.57KB
015 Importing-Text-Data-with-NumPy-Template.ipynb	2.27KB
015 iris-dataset.csv	2.40KB
015 iris-with-answers.csv	3.63KB
015 Lending-Company-Numeric-Data.csv	29.54KB
015 Lending-Company-Numeric-Data-NAN.csv	28.64KB
015 Logistic-Regression.url	159B
015 Logistic-Regression-with-Comments.url	173B
015 More on Dummy Variables A Statistical Perspective_en.srt	2.02KB
015 More on Dummy Variables A Statistical Perspective.mp4	5.82MB
015 SKLEAR-1.IPY	16.79KB
015 sklearn-Feature-Selection-through-Feature-Scaling-Standardization-Part-2.ipynb	14.89KB
015 Species-Segmentation-with-Cluster-Analysis-Part-2-Exercise.ipynb	10.74KB
015 Species-Segmentation-with-Cluster-Analysis-Part-2-Solution.ipynb	15.30KB
015 Test for the mean. Independent Samples (Part 2). Exercise.html	81B
015 Testing the Model_en.srt	7.84KB
015 Testing-the-model.ipynb	5.77KB
015 Testing the Model.mp4	21.59MB
015 Testing-the-model-with-comments.ipynb	7.56KB
015 Variance_en.srt	9.86KB
015 Variance.mp4	23.54MB
016 1.02.Multiple-linear-regression.csv	1.07KB
016 2.9.Variance-exercise.xlsx	10.83KB
016 2.9.Variance-exercise-solution.xlsx	11.05KB
016 Bank-data.csv	19.55KB
016 Bank-data-testing.csv	8.30KB
016 Classifying the Various Reasons for Absence_en.srt	12.70KB
016 Classifying the Various Reasons for Absence.mp4	59.20MB
016 Importing Data - Partial Cleaning While Importing Data_en.srt	11.69KB
016 Importing Data - Partial Cleaning While Importing Data.mp4	43.91MB
016 Predicting with the Standardized Coefficients_en.srt	6.64KB
016 Predicting with the Standardized Coefficients.mp4	20.42MB
016 Preparing the Deployment of the Model through a Module_en.srt	7.12KB
016 sklearn-Making-Predictions-with-the-Standardized-Coefficients.ipynb	29.75KB
016 sklearn-Making-Predictions-with-the-Standardized-Coefficients-with-comments.ipynb	22.03KB
016 Testing the Model - Exercise.html	87B
016 Testing-the-Model-Exercise.ipynb	6.79KB
016 Testing-the-Model-Solution.ipynb	111.10KB
016 Variance Exercise.html	522B
017 2.10.Standard-deviation-and-coefficient-of-variation-lesson.xlsx	10.97KB
017 Feature Scaling (Standardization) - Exercise.html	76B
017 Importing Data with NumPy - Exercise.html	308B
017 Importing-Text-Data-DSc-Exercise.ipynb	4.18KB
017 Importing-Text-Data-DSc-Solution.ipynb	24.39KB
017 real-estate-price-size-year.csv	2.35KB
017 sklearn-Feature-Scaling-Exercise.ipynb	6.07KB
017 sklearn-Feature-Scaling-Exercise-Solution.ipynb	16.28KB
017 Standard Deviation and Coefficient of Variation_en.srt	7.59KB
017 Standard Deviation and Coefficient of Variation.mp4	20.14MB
017 Using .concat() in Python_en.srt	6.19KB
017 Using .concat() in Python.mp4	27.33MB
018 2.10.Standard-deviation-and-coefficient-of-variation-exercise.xlsx	11.61KB
018 2.10.Standard-deviation-and-coefficient-of-variation-exercise-solution.xlsx	12.60KB
018 EXERCISE - Using .concat() in Python.html	189B
018 Importing Data from .json Files_en.srt	9.08KB
018 Importing Data from .json Files.mp4	81.95MB
018 Lending-company.json	213.54KB
018 Standard Deviation and Coefficient of Variation Exercise.html	81B
018 Underfitting and Overfitting_en.srt	4.51KB
018 Underfitting and Overfitting.mp4	5.83MB
019 2.11.Covariance-lesson.xlsx	24.92KB
019 An Introduction to Working with Excel Files in Python_en.srt	6.64KB
019 An Introduction to Working with Excel Files in Python.mp4	42.98MB
019 Covariance_en.srt	6.14KB
019 Covariance.mp4	18.38MB
019 sklearn-Train-Test-Split.ipynb	7.23KB
019 sklearn-Train-Test-Split-with-comments.ipynb	9.05KB
019 SOLUTION - Using .concat() in Python.html	143B
019 Train - Test Split Explained_en.srt	11.71KB
019 Train - Test Split Explained.mp4	35.57MB
020 2.11.Covariance-exercise.xlsx	20.23KB
020 2.11.Covariance-exercise-solution.xlsx	29.51KB
020 Covariance Exercise.html	81B
020 Lending-company.xlsx	93.06KB
020 Reordering Columns in a Pandas DataFrame in Python_en.srt	2.22KB
020 Reordering Columns in a Pandas DataFrame in Python.mp4	9.99MB
020 Working with Excel (.xlsx) Data_en.srt	3.35KB
020 Working with Excel (.xlsx) Data.mp4	14.41MB
021 Correlation Coefficient_en.srt	5.94KB
021 Correlation Coefficient.mp4	19.34MB
021 EXERCISE - Reordering Columns in a Pandas DataFrame in Python.html	161B
021 Importing Data in Python - an Important Exercise_en.srt	10.00KB
021 Importing Data in Python - an Important Exercise.mp4	43.01MB
022 2.12.Correlation-exercise.xlsx	29.30KB
022 2.12.Correlation-exercise-solution.xlsx	29.48KB
022 Correlation Coefficient Exercise.html	81B
022 Customer-Gender.csv	7.45KB
022 Importing Data with the .squeeze() Method_en.srt	5.50KB
022 Importing Data with the .squeeze() Method.mp4	22.42MB
022 Importing-Data-with-the-pandas-Squeeze-Method.ipynb	20.15KB
022 SOLUTION - Reordering Columns in a Pandas DataFrame in Python.html	478B
023 Absenteeism-Exercise-Preprocessing-df-reason-mod.ipynb	4.82KB
023 Creating Checkpoints while Coding in Jupyter_en.srt	4.32KB
023 Creating Checkpoints while Coding in Jupyter.mp4	17.33MB
023 Importing Files in Jupyter_en.srt	5.79KB
023 Importing Files in Jupyter.mp4	19.57MB
024 EXERCISE - Creating Checkpoints while Coding in Jupyter.html	137B
024 Saving Your Data with pandas_en.srt	5.77KB
024 Saving Your Data with pandas.mp4	21.06MB
025 Lending-Company-Saving.csv	58.40KB
025 Saving-Data-NP-Complete.ipynb	9.83KB
025 Saving-Data-NP-Template.ipynb	3.17KB
025 Saving Your Data with NumPy - Part I - .npy_en.srt	9.10KB
025 Saving Your Data with NumPy - Part I - .npy.mp4	18.91MB
025 SOLUTION - Creating Checkpoints while Coding in Jupyter.html	118B
026 Analyzing the Dates from the Initial Data Set_en.srt	10.63KB
026 Analyzing the Dates from the Initial Data Set.mp4	40.13MB
026 Saving Your Data with NumPy - Part II - .npz_en.srt	7.99KB
026 Saving Your Data with NumPy - Part II - .npz.mp4	23.26MB
027 Extracting the Month Value from the Date Column_en.srt	9.61KB
027 Extracting the Month Value from the Date Column.mp4	33.93MB
027 Saving Your Data with NumPy - Part III - .csv_en.srt	6.46KB
027 Saving Your Data with NumPy - Part III - .csv.mp4	20.83MB
028 Extracting the Day of the Week from the Date Column_en.srt	5.78KB
028 Extracting the Day of the Week from the Date Column.mp4	19.11MB
028 Saving-Data-NP-Exercise.ipynb	6.00KB
028 Saving-Data-NP-Solution.ipynb	13.42KB
028 Saving Data with Numpy - Exercise.html	260B
029 Absenteeism-Exercise-Preprocessing-ChP-df-date-reason-mod.ipynb	7.33KB
029 Absenteeism-Exercise-Preprocessing-LECTURES.ipynb	7.60MB
029 Absenteeism-Exercise-Removing-the-Date-Column-SOLUTION.ipynb	8.33KB
029 EXERCISE - Removing the Date Column.html	1.14KB
029 Working with Text Files in Python - Conclusion_en.srt	1.34KB
029 Working with Text Files in Python - Conclusion.mp4	2.11MB
029 Working-with-Text-Files-Lectures.ipynb	27.58KB
030 Analyzing Several Straightforward Columns for this Exercise_en.srt	5.49KB
030 Analyzing Several Straightforward Columns for this Exercise.mp4	20.09MB
031 Working on Education, Children, and Pets_en.srt	7.19KB
031 Working on Education, Children, and Pets.mp4	16.92MB
032 Absenteeism-Exercise-EXERCISES-and-SOLUTIONS.ipynb	4.13KB
032 Absenteeism-Exercise-Preprocessing-df-preprocessed.ipynb	8.51KB
032 Final Remarks of this Section_en.srt	3.20KB
032 Final Remarks of this Section.mp4	19.74MB
033 A Note on Exporting Your Data as a .csv File.html	880B
external-links.txt	105B
external-links.txt	134B
external-links.txt	790B
external-links.txt	124B
index_13040208.mpd	41.14KB
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Monsters at Work (Monsters.at.Work.S01E07.1080p.WEB-DL.DUAL)	1.21GB
The Boss Baby: Back in Business ({WWW.BLUDV.TV} O Chefinho - De Volta aos Negócios 2018 2ª Temporada Completa (720p) Acesse o ORIGINAL WW.BLUDV.TV)	6.66GB
Algorithmic Stock Trading and Equity Investing with Python	11.95GB
The Essentials of Machine Learning in Finance and Accounting	17.15MB
Monsters at Work (Monsters.At.Work.S01E08.1080pWEB-DL.DUAL)	592.43MB
Monsters at Work (Monsters.at.Work.S01E06.1080p.WEB-DL.DUAL.5.1)	1.10GB
Introduction to Computational Finance and Financial Econometrics	3.91GB
Sharkdog (Sharkdog.S03.1080p.NF.WEBRip.DDP5.1.x264-WDYM[rartv])	5.91GB
Monsters at Work (Monstros no Trabalho S01E04 WEB-DL 1080p DUAL 5.1)	1.05GB
Monsters at Work (Monsters.At.Work.S01E10.1080p.WEBRip.DUAL)	550.74MB

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