Complete Machine Learning and Data Science Zero to Mastery

  05 Data Science Environment Setup

   031 Section Overview.en.srt

   032 Introducing Our Tools.en.srt

   033 conda-cheatsheet.pdf

   033 What is Conda.mp4

   034 Conda Environments.mp4

   035 Mac Environment Setup.mp4

   036 Mac Environment Setup 2.mp4

   037 Windows Environment Setup.mp4

   039 Linux Environment Setup.html

   041 6-step-ml-framework.png

   041 Jupyter Notebook Walkthrough.en.srt

   042 Jupyter Notebook Walkthrough 2.en.srt

   043 Jupyter Notebook Walkthrough 3.en.srt

   external-assets-links.txt

  ReadMe.txt

  01 Introduction

   001 Course Outline.mp4

   003 Exercise Meet The Community.html

   004 Your First Day.mp4

   Visit Coursedrive.org.url

  02 Machine Learning 101

   005 What Is Machine Learning.mp4

   006 AIMachine LearningData Science.mp4

   007 Exercise Machine Learning Playground.mp4

   008 How Did We Get Here.mp4

   009 Exercise YouTube Recommendation Engine.mp4

   010 Types of Machine Learning.mp4

   012 What Is Machine Learning Round 2.en.srt

   013 Section Review.en.srt

   external-assets-links.txt

  03 Machine Learning and Data Science Framework

   014 Section Overview.mp4

   015 Introducing Our Framework.mp4

   016 6 Step Machine Learning Framework.mp4

   017 Types of Machine Learning Problems.mp4

   018 Types of Data.mp4

   019 Types of Evaluation.mp4

   020 Features In Data.mp4

   021 Modelling - Splitting Data.mp4

   022 Modelling - Picking the Model.mp4

   023 Modelling - Tuning.mp4

   024 Modelling - Comparison.mp4

   026 Experimentation.en.srt

   027 Tools We Will Use.en.srt

   028 Optional Elements of AI.html

  04 The 2 Paths

   029 The 2 Paths.mp4

  06 Pandas Data Analysis

   044 Section Overview.mp4

   046 Pandas Introduction.mp4

   047 Series Data Frames and CSVs.en.srt

   048 Data from URLs.html

   049 Describing Data with Pandas.mp4

   050 Selecting and Viewing Data with Pandas.en.srt

   051 Selecting and Viewing Data with Pandas Part 2.en.srt

   052 car-sales-missing-data.csv

   052 Manipulating Data.mp4

   053 Manipulating Data 2.mp4

   054 Manipulating Data 3.en.srt

   055 Assignment Pandas Practice.html

   056 How To Download The Course Assignments.mp4

  07 NumPy

   057 Section Overview.mp4

   058 NumPy Introduction.mp4

   060 NumPy DataTypes and Attributes.en.srt

   061 Creating NumPy Arrays.en.srt

   062 NumPy Random Seed.en.srt

   063 Viewing Arrays and Matrices.en.srt

   064 Manipulating Arrays.en.srt

   065 Manipulating Arrays 2.en.srt

   066 Standard Deviation and Variance.en.srt

   067 Reshape and Transpose.en.srt

   068 Dot Product vs Element Wise.en.srt

   069 Exercise Nut Butter Store Sales.en.srt

   070 Comparison Operators.en.srt

   071 Sorting Arrays.en.srt

   072 numpy-images.zip

   072 Turn Images Into NumPy Arrays.mp4

   074 Optional Extra NumPy resources.html

  08 Matplotlib Plotting and Data Visualization

   075 Section Overview.mp4

   076 Matplotlib Introduction.mp4

   077 Importing And Using Matplotlib.mp4

   078 Anatomy Of A Matplotlib Figure.mp4

   078 matplotlib-anatomy-of-a-plot.png

   079 Scatter Plot And Bar Plot.mp4

   080 Histograms And Subplots.mp4

   081 Subplots Option 2.mp4

   082 Quick Tip Data Visualizations.mp4

   083 Plotting From Pandas DataFrames.mp4

   085 Plotting From Pandas DataFrames 2.en.srt

   086 Plotting from Pandas DataFrames 3.en.srt

   087 heart-disease.csv

   087 Plotting from Pandas DataFrames 4.mp4

   088 Plotting from Pandas DataFrames 5.mp4

   089 Plotting from Pandas DataFrames 6.mp4

   090 Plotting from Pandas DataFrames 7.mp4

   091 Customizing Your Plots.mp4

   092 Customizing Your Plots 2.mp4

   093 Saving And Sharing Your Plots.mp4

   external-assets-links.txt

  09 Scikit-learn Creating Machine Learning Models

   095 Section Overview.mp4

   096 Scikit-learn Introduction.mp4

   098 Refresher What Is Machine Learning.en.srt

   099 Quick Note Upcoming Videos.html

   100 Scikit-learn Cheatsheet.mp4

   101 Typical scikit-learn Workflow.mp4

   102 Optional Debugging Warnings In Jupyter.mp4

   103 Getting Your Data Ready Splitting Your Data.mp4

   104 Quick Tip Clean Transform Reduce.en.srt

   105 Getting Your Data Ready Convert Data To Numbers.en.srt

   106 Getting Your Data Ready Handling Missing Values With Pandas.en.srt

   107 Note Correction in the upcoming video (splitting data).html

   108 Getting Your Data Ready Handling Missing Values With Scikit-learn.mp4

   109 Choosing The Right Model For Your Data.mp4

   110 Choosing The Right Model For Your Data 2 (Regression).mp4

   112 Quick Tip How ML Algorithms Work.en.srt

   113 Choosing The Right Model For Your Data 3 (Classification).en.srt

   114 Fitting A Model To The Data.en.srt

   115 Making Predictions With Our Model.en.srt

   116 predict() vs predict_proba().en.srt

   117 Making Predictions With Our Model (Regression).en.srt

   118 Evaluating A Machine Learning Model (Score).en.srt

   119 Evaluating A Machine Learning Model 2 (Cross Validation).en.srt

   120 Evaluating A Classification Model 1 (Accuracy).en.srt

   121 Evaluating A Classification Model 2 (ROC Curve).en.srt

   122 Evaluating A Classification Model 3 (ROC Curve).en.srt

   123 Evaluating A Classification Model 4 (Confusion Matrix).en.srt

   124 Evaluating A Classification Model 5 (Confusion Matrix).en.srt

   125 Evaluating A Classification Model 6 (Classification Report).en.srt

   126 Evaluating A Regression Model 1 (R2 Score).en.srt

   127 Evaluating A Regression Model 2 (MAE).en.srt

   128 Evaluating A Regression Model 3 (MSE).en.srt

   129 Machine Learning Model Evaluation.html

   130 Evaluating A Model With Cross Validation and Scoring Parameter.mp4

   131 Evaluating A Model With Scikit-learn Functions.mp4

   132 Improving A Machine Learning Model.mp4

   133 Tuning Hyperparameters.mp4

   134 Tuning Hyperparameters 2.mp4

   135 Tuning Hyperparameters 3.mp4

   136 Quick Tip Correlation Analysis.mp4

   137 Saving And Loading A Model.mp4

   138 Saving And Loading A Model 2.mp4

   139 Putting It All Together.mp4

   140 Putting It All Together 2.mp4

   external-assets-links.txt

  10 Supervised Learning Classification Regression

  11 Milestone Project 1 Supervised Learning (Classification)

   143 Section Overview.mp4

   144 Project Overview.mp4

   145 Project Environment Setup.mp4

   146 Step 1~4 Framework Setup.mp4

   147 Getting Our Tools Ready.mp4

   148 Exploring Our Data.mp4

   149 Finding Patterns.en.srt

   150 Finding Patterns 2.en.srt

   151 Finding Patterns 3.en.srt

   152 Preparing Our Data For Machine Learning.en.srt

   153 Choosing The Right Models.en.srt

   154 Experimenting With Machine Learning Models.en.srt

   155 TuningImproving Our Model.en.srt

   156 Tuning Hyperparameters.en.srt

   157 Tuning Hyperparameters 2.en.srt

   158 Tuning Hyperparameters 3.en.srt

   159 Evaluating Our Model.en.srt

   160 Evaluating Our Model 2.en.srt

   161 Evaluating Our Model 3.en.srt

   162 Finding The Most Important Features.en.srt

   163 Reviewing The Project.en.srt

   external-assets-links.txt

  12 Milestone Project 2 Supervised Learning (Time Series Data)

   164 Section Overview.mp4

   165 Project Overview.mp4

   166 Project Environment Setup.mp4

   167 Step 1~4 Framework Setup.mp4

   168 Exploring Our Data.mp4

   169 Exploring Our Data 2.mp4

   170 Feature Engineering.mp4

   171 Turning Data Into Numbers.mp4

   172 Filling Missing Numerical Values.mp4

   173 Filling Missing Categorical Values.mp4

   174 Fitting A Machine Learning Model.mp4

   175 Splitting Data.mp4

   177 Custom Evaluation Function.en.srt

   178 Reducing Data.en.srt

   179 RandomizedSearchCV.en.srt

   180 Improving Hyperparameters.en.srt

   181 Preproccessing Our Data.en.srt

   182 Making Predictions.en.srt

   183 Feature Importance.en.srt

   external-assets-links.txt

  13 Data Engineering

   184 Data Engineering Introduction.mp4

   185 What Is Data.mp4

   186 What Is A Data Engineer.mp4

   187 What Is A Data Engineer 2.mp4

   188 What Is A Data Engineer 3.mp4

   189 What Is A Data Engineer 4.mp4

   190 Types Of Databases.mp4

   192 Optional OLTP Databases.en.srt

   193 Optional Learn SQL.html

   194 Hadoop HDFS and MapReduce.mp4

   195 Apache Spark and Apache Flink.mp4

   196 Kafka and Stream Processing.mp4

  14 Neural Networks Deep Learning Transfer Learning and TensorFlow 2

   197 Section Overview.mp4

   198 Deep Learning and Unstructured Data.mp4

   200 Setting Up Google Colab.en.srt

   201 Google Colab Workspace.en.srt

   202 Uploading Project Data.en.srt

   203 Setting Up Our Data.en.srt

   204 Setting Up Our Data 2.en.srt

   205 Importing TensorFlow 2.en.srt

   206 Optional TensorFlow 2.0 Default Issue.en.srt

   207 Using A GPU.en.srt

   208 Optional GPU and Google Colab.en.srt

   209 Optional Reloading Colab Notebook.en.srt

   210 Loading Our Data Labels.en.srt

   211 Preparing The Images.en.srt

   212 Turning Data Labels Into Numbers.en.srt

   213 Creating Our Own Validation Set.en.srt

   214 Preprocess Images.en.srt

   215 Preprocess Images 2.en.srt

   216 Turning Data Into Batches.en.srt

   217 Turning Data Into Batches 2.en.srt

   218 Visualizing Our Data.en.srt

   219 Preparing Our Inputs and Outputs.en.srt

   220 Optional How machines learn and whats going on behind the scenes.html

   221 Building A Deep Learning Model.mp4

   222 Building A Deep Learning Model 2.mp4

   223 Building A Deep Learning Model 3.mp4

   224 Building A Deep Learning Model 4.mp4

   225 Summarizing Our Model.mp4

   226 Evaluating Our Model.mp4

   227 Preventing Overfitting.mp4

   228 Training Your Deep Neural Network.mp4

   229 Evaluating Performance With TensorBoard.mp4

   230 Make And Transform Predictions.mp4

   231 Transform Predictions To Text.mp4

   232 Visualizing Model Predictions.mp4

   233 Visualizing And Evaluate Model Predictions 2.mp4

   234 Visualizing And Evaluate Model Predictions 3.mp4

   235 Saving And Loading A Trained Model.mp4

   236 Training Model On Full Dataset.mp4

   237 Making Predictions On Test Images.mp4

   238 Submitting Model to Kaggle.mp4

   239 Making Predictions On Our Images.mp4

   external-assets-links.txt

  15 Storytelling Communication How To Present Your Work

   241 Section Overview.mp4

   242 Communicating Your Work.mp4

   243 Communicating With Managers.mp4

   244 Communicating With Co-Workers.mp4

   245 Weekend Project Principle.mp4

   246 Communicating With Outside World.mp4

   247 Storytelling.mp4

   external-assets-links.txt

  16 Career Advice Extra Bits

   250 Quick Note Upcoming Video.html

   251 What If I Dont Have Enough Experience.mp4

   253 Quick Note Upcoming Videos.html

   254 JTS Learn to Learn.mp4

   255 JTS Start With Why.mp4

   257 CWD Git Github.en.srt

   258 CWD Git Github 2.en.srt

   259 Contributing To Open Source.en.srt

   260 Contributing To Open Source 2.en.srt

   261 Coding Challenges.html

  17 Learn Python

   263 What Is A Programming Language.mp4

   264 Python Interpreter.mp4

   265 How To Run Python Code.mp4

   266 Our First Python Program.mp4

   267 Python 2 vs Python 3.mp4

   268 Exercise How Does Python Work.mp4

   269 Learning Python.mp4

   270 Python Data Types.mp4

   272 Numbers.en.srt

   273 Math Functions.en.srt

   274 DEVELOPER FUNDAMENTALS I.en.srt

   275 Operator Precedence.en.srt

   276 Exercise Operator Precedence.html

   277 Optional bin() and complex.mp4

   278 Variables.mp4

   279 Expressions vs Statements.mp4

   280 Augmented Assignment Operator.mp4

   281 Strings.mp4

   282 String Concatenation.mp4

   283 Type Conversion.mp4

   284 Escape Sequences.mp4

   285 Formatted Strings.mp4

   286 String Indexes.mp4

   287 Immutability.mp4

   288 Built-In Functions Methods.mp4

   289 Booleans.mp4

   290 Exercise Type Conversion.mp4

   291 DEVELOPER FUNDAMENTALS II.mp4

   292 Exercise Password Checker.mp4

   293 Lists.mp4

   294 List Slicing.mp4

   295 Matrix.mp4

   296 List Methods.mp4

   297 List Methods 2.mp4

   298 List Methods 3.mp4

   299 Common List Patterns.mp4

   300 List Unpacking.mp4

   301 None.mp4

   302 Dictionaries.mp4

   303 DEVELOPER FUNDAMENTALS III.mp4

   304 Dictionary Keys.mp4

   305 Dictionary Methods.mp4

   306 Dictionary Methods 2.mp4

   307 Tuples.mp4

   308 Tuples 2.mp4

   309 Sets.mp4

   310 Sets 2.mp4

  18 Learn Python Part 2

   311 Breaking The Flow.mp4

   312 Conditional Logic.mp4

   313 Indentation In Python.mp4

   314 Truthy vs Falsey.mp4

   315 Ternary Operator.mp4

   316 Short Circuiting.mp4

   317 Logical Operators.mp4

   318 Exercise Logical Operators.mp4

   319 is vs.mp4

   320 For Loops.mp4

   321 Iterables.mp4

   322 Exercise Tricky Counter.mp4

   323 range().mp4

   324 enumerate().mp4

   325 While Loops.mp4

   326 While Loops 2.mp4

   327 break continue pass.mp4

   328 Our First GUI.mp4

   329 DEVELOPER FUNDAMENTALS IV.mp4

   330 Exercise Find Duplicates.mp4

   331 Functions.mp4

   332 Parameters and Arguments.mp4

   333 Default Parameters and Keyword Arguments.mp4

   334 return.mp4

   336 Methods vs Functions.en.srt

   337 Docstrings.en.srt

   338 Clean Code.en.srt

   339 args and kwargs.en.srt

   340 Exercise Functions.en.srt

   341 Scope.en.srt

   342 Scope Rules.en.srt

   343 global Keyword.en.srt

   344 nonlocal Keyword.en.srt

   345 Why Do We Need Scope.en.srt

   346 Pure Functions.en.srt

   347 map().en.srt

   348 filter().en.srt

   349 zip().en.srt

   350 reduce().en.srt

   351 List Comprehensions.en.srt

   352 Set Comprehensions.en.srt

   353 Exercise Comprehensions.en.srt

   354 Python Exam Testing Your Understanding.html

   355 Modules in Python.mp4

   357 Optional PyCharm.en.srt

   358 Packages in Python.en.srt

   359 Different Ways To Import.en.srt

   360 Next Steps.html

  19 Bonus Learn Advanced Statistics and Mathematics for FREE

  20 Where To Go From Here

   363 Thank You.en.srt

  21 Extras

   ReadMe.txt

 Visit Coursedrive.org.url