udemy-机器学习和数据科学训练营Complete Machine Learning & Data Science Bootcamp 4 - The 2 Paths 6 - Pandas Data Analysis 20 - Where To Go From Here 12 - Milestone Project 2 Supervised Learning Time Series Data 1 - Introduction 10 - Supervised Learning Classification Regression 9 - Scikitlearn Creating Machine Learning Models 21 - BONUS SECTION 18 - Learn Python Part 2 1 - Introduction 16 - Career Advice Extra Bits 11 - Milestone Project 1 Supervised Learning Classification 8 - Matplotlib Plotting and Data Visualization 19 - Extra Learn Advanced Statistics and Mathematics for FREE 14 - Neural Networks Deep Learning Transfer Learning and TensorFlow 2 7 - NumPy 2 - Machine Learning 101 13 - Data Engineering 5 - Data Science Environment Setup 17 - Learn Python 15 - Storytelling Communication How To Present Your Work 3 - Machine Learning and Data Science Framework 48 - Pandas Documentation.txt 48 - Pandas Introduction.srt 57 - Assignment Pandas Practice.html 52 - car-sales.csv 55 - Manipulating Data 2.srt 49 - Series Data Frames and CSVs.srt 56 - Manipulating Data 3.srt 58 - How To Download The Course Assignments.srt 49 - car-sales.csv 52 - Selecting and Viewing Data with Pandas.mp4 56 - Manipulating Data 3.mp4 52 - Selecting and Viewing Data with Pandas.srt 46 - Section Overview.mp4 54 - Manipulating Data.srt 51 - Describing Data with Pandas.mp4 56 - Introduction to Pandas Jupyter Notebook from the videos.txt 48 - Introduction to Pandas Jupyter Notebook with annotations.txt 46 - Section Overview.srt 55 - pandas-anatomy-of-a-dataframe.png 58 - Course notebooks Github.txt 48 - Pandas Introduction.mp4 51 - Describing Data with Pandas.srt 53 - Selecting and Viewing Data with Pandas Part 2.mp4 55 - Manipulating Data 2.mp4 56 - Introduction to Pandas Jupyter Notebook with annotations.txt 47 - Downloading Workbooks and Assignments.html 54 - Manipulating Data.mp4 58 - How To Download The Course Assignments.mp4 49 - pandas-anatomy-of-a-dataframe.png 50 - Data from URLs.html 49 - Series Data Frames and CSVs.mp4 48 - 10 minutes to pandas from the documentation.txt 48 - Introduction to Pandas Jupyter Notebook from the upcoming videos.txt 54 - car-sales-missing-data.csv 58 - Google Colab.txt 53 - Selecting and Viewing Data with Pandas Part 2.srt 54 - Jake VanderPlass Data Manipulation with Pandas.txt 32 - Endorsements On LinkedIN.html 31 - Python Machine Learning Monthly.html 30 - The 2 Paths.mp4 30 - The 2 Paths.srt 376 - Thank You.mp4 375 - Become An Alumni.html 377 - Thank You Part 2.html 376 - Thank You.srt 194 - Endtoend Bluebook Bulldozer Regression Notebook same as in videos.txt 181 - Feature Engineering.mp4 193 - Making Predictions.mp4 188 - Custom Evaluation Function.mp4 194 - Feature Importance.srt 175 - Structured Data Projects on GitHub.txt 185 - Fitting A Machine Learning Model.srt 194 - Feature Importance.mp4 189 - Reducing Data.srt 177 - Project Environment Setup.srt 193 - Making Predictions.srt 184 - Filling Missing Categorical Values.srt 183 - Pandas Categorical Datatype Documentation.txt 175 - Endtoend Bluebook Bulldozer Regression Notebook same as in videos.txt 183 - Filling Missing Numerical Values.srt 191 - Improving Hyperparameters.srt 186 - Splitting Data.mp4 179 - Exploring Our Data.srt 181 - Feature Engineering.srt 191 - Improving Hyperparameters.mp4 192 - Preproccessing Our Data.srt 178 - Step 14 Framework Setup.srt 184 - Filling Missing Categorical Values.mp4 176 - Downloading the data for the next two projects.html 175 - Project Overview.srt 189 - Reducing Data.mp4 174 - Section Overview.mp4 185 - Fitting A Machine Learning Model.mp4 187 - Challenge Whats wrong with splitting data after filling it.html 180 - Exploring Our Data 2.srt 179 - Exploring Our Data.mp4 183 - Filling Missing Numerical Values.mp4 186 - Splitting Data.srt 182 - Turning Data Into Numbers.srt 174 - Section Overview.srt 188 - Custom Evaluation Function.srt 194 - Endtoend Bluebook Bulldozer Regression Notebook with annotations.txt 192 - Preproccessing Our Data.mp4 175 - Project Overview.mp4 190 - RandomizedSearchCV.srt 190 - RandomizedSearchCV.mp4 182 - Turning Data Into Numbers.mp4 175 - Kaggle Bluebook for Bulldozers Competition.txt 177 - Project Environment Setup.mp4 175 - Endtoend Bluebook Bulldozer Regression Notebook with annotations.txt 178 - Step 14 Framework Setup.mp4 180 - Exploring Our Data 2.mp4 378 - Special Bonus Lecture.html 150 - Milestone Projects.html 1 - Course Outline.srt 142 - Tuning Hyperparameters 3.srt 133 - NEW Evaluating A Regression Model 1 R2 Score.mp4 132 - Evaluating A Classification Model 6 Classification Report.mp4 145 - Saving And Loading A Model.srt 125 - Evaluating A Machine Learning Model 2 Cross Validation.mp4 149 - ScikitLearn Practice.html 147 - Reading extension ScikitLearns Pipeline class explained.txt 103 - Scikitlearn Cheatsheet.mp4 103 - Scikitlearn Cheatsheet.srt 131 - NEW Evaluating A Classification Model 5 Confusion Matrix.srt 122 - NEW Making Predictions With Our Model Regression.mp4 114 - NEW Choosing The Right Model For Your Data.srt 122 - NEW Making Predictions With Our Model Regression.srt 148 - Putting It All Together 2.srt 118 - Choosing The Right Model For Your Data 3 Classification.srt 104 - Typical scikitlearn Workflow.srt 146 - Saving And Loading A Model 2.srt 127 - Evaluating A Classification Model 2 ROC Curve.srt 119 - Fitting A Model To The Data.srt 128 - Evaluating A Classification Model 3 ROC Curve.srt 114 - NEW Choosing The Right Model For Your Data.mp4 129 - Reading Extension ROC Curve AUC.html 119 - Fitting A Model To The Data.mp4 130 - Evaluating A Classification Model 4 Confusion Matrix.mp4 107 - Quick Tip Clean Transform Reduce.srt 101 - Refresher What Is Machine Learning.mp4 130 - Evaluating A Classification Model 4 Confusion Matrix.srt 128 - Evaluating A Classification Model 3 ROC Curve.mp4 106 - Getting Your Data Ready Splitting Your Data.srt 139 - Improving A Machine Learning Model.mp4 147 - Putting It All Together.srt 109 - Note Update to next video OneHotEncoder can handle NaNNone values.html 108 - Getting Your Data Ready Convert Data To Numbers.srt 115 - NEW Choosing The Right Model For Your Data 2 Regression.mp4 127 - Evaluating A Classification Model 2 ROC Curve.mp4 116 - Quick Note Decision Trees.html 141 - Tuning Hyperparameters 2.mp4 139 - Improving A Machine Learning Model.srt 99 - Introduction to ScikitLearn Jupyter Notebook from the upcoming videos.txt 142 - Tuning Hyperparameters 3.mp4 106 - scikit-learn-data.zip 111 - Extension Feature Scaling.html 112 - Note Correction in the upcoming video splitting data.html 108 - Getting Your Data Ready Convert Data To Numbers.mp4 147 - Putting It All Together.mp4 117 - Quick Tip How ML Algorithms Work.mp4 125 - Evaluating A Machine Learning Model 2 Cross Validation.srt 141 - Tuning Hyperparameters 2.srt 148 - Introduction to ScikitLearn Jupyter Notebook with annotations.txt 140 - Tuning Hyperparameters.mp4 104 - Typical scikitlearn Workflow.mp4 117 - Quick Tip How ML Algorithms Work.srt 99 - ScikitLearn Documentation.txt 137 - NEW Evaluating A Model With Cross Validation and Scoring Parameter.mp4 135 - NEW Evaluating A Regression Model 3 MSE.mp4 130 - Notebook from video with updated confusion matrix labels.txt 121 - predict vs predictproba.mp4 123 - NEW Evaluating A Machine Learning Model Score Part 1.mp4 102 - Quick Note Upcoming Videos.html 107 - Quick Tip Clean Transform Reduce.mp4 120 - Making Predictions With Our Model.mp4 148 - Introduction to ScikitLearn Jupyter Notebook from the videos.txt 131 - NEW Evaluating A Classification Model 5 Confusion Matrix.mp4 123 - NEW Evaluating A Machine Learning Model Score Part 1.srt 138 - NEW Evaluating A Model With Scikitlearn Functions.mp4 137 - NEW Evaluating A Model With Cross Validation and Scoring Parameter.srt 144 - Quick Tip Correlation Analysis.mp4 135 - NEW Evaluating A Regression Model 3 MSE.srt 98 - Section Overview.mp4 134 - NEW Evaluating A Regression Model 2 MAE.srt 124 - NEW Evaluating A Machine Learning Model Score Part 2.srt 110 - Getting Your Data Ready Handling Missing Values With Pandas.srt 145 - Saving And Loading A Model.mp4 105 - Optional Debugging Warnings In Jupyter.mp4 126 - Evaluating A Classification Model 1 Accuracy.mp4 144 - Quick Tip Correlation Analysis.srt 140 - Tuning Hyperparameters.srt 132 - Evaluating A Classification Model 6 Classification Report.srt 146 - Saving And Loading A Model 2.mp4 121 - predict vs predictproba.srt 105 - Optional Debugging Warnings In Jupyter.srt 134 - NEW Evaluating A Regression Model 2 MAE.mp4 100 - Quick Note Upcoming Video.html 124 - NEW Evaluating A Machine Learning Model Score Part 2.mp4 118 - Choosing The Right Model For Your Data 3 Classification.mp4 103 - ScikitLearn Reference Notebook.txt 106 - Getting Your Data Ready Splitting Your Data.mp4 99 - Scikitlearn Introduction.mp4 133 - NEW Evaluating A Regression Model 1 R2 Score.srt 120 - Making Predictions With Our Model.srt 113 - Getting Your Data Ready Handling Missing Values With Scikitlearn.mp4 101 - Refresher What Is Machine Learning.srt 115 - NEW Choosing The Right Model For Your Data 2 Regression.srt 99 - Scikitlearn Introduction.srt 113 - Getting Your Data Ready Handling Missing Values With Scikitlearn.srt 104 - Example ScikitLearn Workflow Notebook.txt 126 - Evaluating A Classification Model 1 Accuracy.srt 110 - Getting Your Data Ready Handling Missing Values With Pandas.mp4 114 - ScikitLearn machine learning map how to choose the right machine learning model【微信号 itcodeba 】【更多教程 todo1024.com】.txt 143 - Note Metric Comparison Improvement.html 148 - Putting It All Together 2.mp4 99 - Introduction to ScikitLearn Jupyter Notebook with annotations.txt 138 - NEW Evaluating A Model With Scikitlearn Functions.srt 136 - Machine Learning Model Evaluation.html 98 - Section Overview.srt 264 - Quick Note Upcoming Videos.html 270 - Contributing To Open Source.srt 265 - JTS Learn to Learn.mp4 272 - Exercise Contribute To Open Source.html 267 - Quick Note Upcoming Videos.html 263 - Learning Guideline.html 268 - CWD Git Github.mp4 270 - Contributing To Open Source.mp4 271 - Contributing To Open Source 2.srt 266 - JTS Start With Why.mp4 268 - CWD Git Github.srt 269 - CWD Git Github 2.mp4 273 - Coding Challenges.html 271 - Contributing To Open Source 2.mp4 269 - CWD Git Github 2.srt 260 - Endorsements On LinkedIn.html 261 - Quick Note Upcoming Video.html 262 - What If I Dont Have Enough Experience.srt 265 - JTS Learn to Learn.srt 266 - JTS Start With Why.srt 262 - What If I Dont Have Enough Experience.mp4 2 - Join Our Online Classroom.mp4 4 - Your First Day.srt 2 - Join Our Online Classroom.srt 1 - Course Outline.mp4 3 - Exercise Meet Your Classmates and Instructor.html 173 - Reviewing The Project.srt 152 - Structured Data Projects on GitHub.txt 163 - Experimenting With Machine Learning Models.mp4 159 - Finding Patterns 2.mp4 169 - Evaluating Our Model.mp4 161 - Preparing Our Data For Machine Learning.srt 165 - Tuning Hyperparameters.mp4 172 - Finding The Most Important Features.mp4 159 - Finding Patterns 2.srt 151 - Section Overview.mp4 169 - Evaluating Our Model.srt 162 - Choosing The Right Models.srt 163 - Experimenting With Machine Learning Models.srt 162 - Choosing The Right Models.mp4 160 - Finding Patterns 3.mp4 167 - Tuning Hyperparameters 3.srt 156 - Getting Our Tools Ready.srt 170 - Evaluating Our Model 2.mp4 167 - Tuning Hyperparameters 3.mp4 156 - Getting Our Tools Ready.mp4 157 - Exploring Our Data.srt 173 - Reviewing The Project.mp4 152 - Endtoend Heart Disease Classification Notebook with annotations.txt 164 - TuningImproving Our Model.mp4 161 - Preparing Our Data For Machine Learning.mp4 158 - Finding Patterns.mp4 173 - Endtoend Heart Disease Classification Notebook same as in videos.txt 164 - TuningImproving Our Model.srt 152 - Project Overview.mp4 158 - Finding Patterns.srt 171 - Evaluating Our Model 3.srt 155 - Step 14 Framework Setup.mp4 152 - Project Overview.srt 157 - Exploring Our Data.mp4 172 - Finding The Most Important Features.srt 160 - Finding Patterns 3.srt 171 - Evaluating Our Model 3.mp4 168 - Quick Note Confusion Matrix Labels.html 154 - Optional Windows Project Environment Setup.srt 166 - Tuning Hyperparameters 2.mp4 151 - Section Overview.srt 153 - Project Environment Setup.mp4 153 - Project Environment Setup.srt 152 - Endtoend Heart Disease Classification Notebook same as in videos.txt 157 - heart-disease.csv 155 - Step 14 Framework Setup.srt 173 - Endtoend Heart Disease Classification Notebook with annotations.txt 165 - Tuning Hyperparameters.srt 154 - Optional Windows Project Environment Setup.mp4 170 - Evaluating Our Model 2.srt 166 - Tuning Hyperparameters 2.srt 338 - While Loops 2.mp4 370 - Packages in Python.mp4 365 - Exercise Repl.txt 342 - Solution Repl.txt 352 - Solution Repl.txt 362 - reduce.srt 331 - is vs.srt 341 - DEVELOPER FUNDAMENTALS IV.srt 342 - Exercise Find Duplicates.mp4 352 - Exercise Functions.srt 369 - Optional PyCharm.mp4 335 - range.srt 368 - Quick Note Upcoming Videos.html 344 - Parameters and Arguments.mp4 340 - Solution Repl.txt 347 - Exercise Tesla.html 333 - Iterables.srt 348 - Methods vs Functions.mp4 356 - nonlocal Keyword.srt 349 - Docstrings.mp4 343 - Functions.mp4 353 - Scope.mp4 357 - Why Do We Need Scope.mp4 362 - reduce.mp4 360 - filter.srt 372 - Next Steps.html 334 - Exercise Tricky Counter.mp4 324 - Conditional Logic.mp4 355 - global Keyword.mp4 326 - Truthy vs Falsey.srt 326 - Truthy vs Falsey Stackoverflow.txt 341 - DEVELOPER FUNDAMENTALS IV.mp4 335 - range.mp4 325 - Indentation In Python.mp4 348 - Methods vs Functions.srt 346 - return.mp4 339 - break continue pass.srt 344 - Parameters and Arguments.srt 361 - zip.srt 328 - Short Circuiting.srt 345 - Default Parameters and Keyword Arguments.mp4 329 - Logical Operators.mp4 323 - Breaking The Flow.mp4 365 - Exercise Comprehensions.srt 327 - Ternary Operator.srt 359 - map.srt 360 - filter.mp4 346 - return.srt 351 - args and kwargs.mp4 364 - Set Comprehensions.srt 333 - Iterables.mp4 323 - Breaking The Flow.srt 327 - Ternary Operator.mp4 353 - Scope.srt 359 - map.mp4 355 - global Keyword.srt 369 - Optional PyCharm.srt 340 - Exercise Repl.txt 366 - Python Exam Testing Your Understanding.html 365 - Exercise Comprehensions.mp4 325 - Indentation In Python.srt 331 - is vs.mp4 326 - Truthy vs Falsey.mp4 324 - Conditional Logic.srt 373 - Bonus Resource Python Cheatsheet.html 356 - nonlocal Keyword.mp4 367 - Modules in Python.mp4 340 - Our First GUI.srt 329 - Logical Operators.srt 349 - Docstrings.srt 367 - Modules in Python.srt 354 - Scope Rules.srt 351 - args and kwargs.srt 336 - enumerate.srt 339 - break continue pass.mp4 350 - Clean Code.srt 342 - Exercise Find Duplicates.srt 350 - Clean Code.mp4 363 - List Comprehensions.srt 356 - Solution Repl.txt 330 - Exercise Logical Operators.srt 340 - Our First GUI.mp4 361 - zip.mp4 334 - Solution Repl.txt 334 - Exercise Tricky Counter.srt 371 - Different Ways To Import.srt 364 - Set Comprehensions.mp4 352 - Exercise Functions.mp4 358 - Pure Functions.srt 336 - enumerate.mp4 370 - Packages in Python.srt 343 - Functions.srt 371 - Different Ways To Import.mp4 338 - While Loops 2.srt 328 - Short Circuiting.mp4 358 - Pure Functions.mp4 345 - Default Parameters and Keyword Arguments.srt 354 - Scope Rules.mp4 330 - Exercise Logical Operators.mp4 332 - For Loops.mp4 337 - While Loops.mp4 332 - For Loops.srt 337 - While Loops.srt 363 - List Comprehensions.mp4 365 - Solution Repl.txt 374 - Statistics and Mathematics.html 74 - numpy-images.zip 70 - Matrix Multiplication Explained.txt 72 - Comparison Operators.mp4 66 - Manipulating Arrays.mp4 62 - NumPy DataTypes and Attributes.mp4 76 - Assignment NumPy Practice.html 61 - Quick Note Correction In Next Video.html 68 - Standard Deviation and Variance.srt 59 - Section Overview.mp4 70 - Dot Product vs Element Wise.srt 67 - Manipulating Arrays 2.srt 77 - Optional Extra NumPy resources.html 75 - Exercise Imposter Syndrome.srt 75 - Exercise Imposter Syndrome.mp4 60 - NumPy Documentation.txt 67 - Manipulating Arrays 2.mp4 59 - Section Overview.srt 69 - Reshape and Transpose.mp4 64 - NumPy Random Seed.mp4 66 - Manipulating Arrays.srt 60 - NumPy Introduction.srt 67 - Standard deviation and variance explained.txt 62 - NumPy DataTypes and Attributes.srt 63 - Creating NumPy Arrays.srt 60 - Introduction to NumPy Jupyter Notebook from the upcoming videos.txt 68 - Standard deviation and variance explained.txt 60 - NumPy Introduction.mp4 73 - Sorting Arrays.srt 74 - Introduction to NumPy Jupyter Notebook with annotations.txt 71 - Exercise Nut Butter Store Sales.mp4 71 - Exercise Nut Butter Store Sales.srt 68 - Standard Deviation and Variance.mp4 70 - Dot Product vs Element Wise.mp4 66 - Standard deviation and variance explained.txt 64 - NumPy Random Seed.srt 63 - Creating NumPy Arrays.mp4 74 - Turn Images Into NumPy Arrays.mp4 65 - Viewing Arrays and Matrices.mp4 60 - Introduction to NumPy Jupyter Notebook with annotations.txt 74 - Introduction to NumPy Jupyter Notebook from the videos.txt 74 - Turn Images Into NumPy Arrays.srt 65 - Viewing Arrays and Matrices.srt 69 - Reshape and Transpose.srt 72 - Comparison Operators.srt 73 - Sorting Arrays.mp4 83 - Histograms And Subplots.mp4 83 - Histograms And Subplots.srt 84 - Subplots Option 2.mp4 95 - Customizing Your Plots 2.srt 81 - Anatomy Of A Matplotlib Figure.srt 81 - matplotlib-anatomy-of-a-plot-with-code.png 97 - Assignment Matplotlib Practice.html 78 - Section Overview.mp4 90 - Plotting from Pandas DataFrames 4.mp4 79 - Matplotlib Introduction.srt 84 - Subplots Option 2.srt 80 - Importing And Using Matplotlib.mp4 79 - Introduction to Matplotlib Jupyter Notebook from the upcoming videos.txt 88 - Plotting From Pandas DataFrames 2.mp4 95 - Customizing Your Plots 2.mp4 94 - Customizing Your Plots.srt 82 - Scatter Plot And Bar Plot.mp4 92 - Plotting from Pandas DataFrames 6.srt 96 - Introduction to Matplotlib Notebook from the videos.txt 87 - Quick Note Regular Expressions.html 91 - Plotting from Pandas DataFrames 5.mp4 89 - Plotting from Pandas DataFrames 3.srt 92 - Plotting from Pandas DataFrames 6.mp4 93 - Plotting from Pandas DataFrames 7.srt 78 - Section Overview.srt 86 - Plotting From Pandas DataFrames.srt 81 - Anatomy Of A Matplotlib Figure.mp4 89 - Plotting from Pandas DataFrames 3.mp4 88 - Plotting From Pandas DataFrames 2.srt 79 - Matplotlib Documentation.txt 94 - Customizing Your Plots.mp4 80 - Importing And Using Matplotlib.srt 85 - Quick Tip Data Visualizations.mp4 96 - Saving And Sharing Your Plots.mp4 90 - heart-disease.csv 91 - Plotting from Pandas DataFrames 5.srt 82 - Scatter Plot And Bar Plot.srt 86 - Plotting From Pandas DataFrames.mp4 79 - Matplotlib Introduction.mp4 90 - Plotting from Pandas DataFrames 4.srt 85 - Quick Tip Data Visualizations.srt 81 - matplotlib-anatomy-of-a-plot.png 93 - Plotting from Pandas DataFrames 7.mp4 96 - Saving And Sharing Your Plots.srt 234 - The Softmax Function activation function we use in our model.txt 212 - Google Colab our workspace for the upcoming project.txt 240 - Evaluating Performance With TensorBoard.mp4 213 - Uploading Project Data.srt 212 - Google Colab Workspace.srt 235 - Article How to choose loss & activation functions when building a deep learning model.txt 235 - Building A Deep Learning Model 4.srt 248 - Making Predictions On Test Images.mp4 217 - Optional TensorFlow 20 Default Issue.srt 243 - Visualizing Model Predictions.mp4 244 - Visualizing And Evaluate Model Predictions 2.mp4 250 - Endtoend Dog Vision Notebook with annotations.txt 227 - Turning Data Into Batches.srt 224 - Blog post by Rachel Thomas of fastai on how and why you should create a validation set.txt 247 - Training Model On Full Dataset.mp4 221 - Loading Our Data Labels.srt 246 - Saving And Loading A Trained Model.srt 221 - Documentation on how many images Google recommends for image problems】.txt 234 - Step by step breakdown of a convolutional neural network what MobileNetV2 is made of.txt 234 - Building A Deep Learning Model 3.mp4 232 - Andrei Karpathys talk on AI at Tesla.txt 231 - Optional How machines learn and whats going on behind the scenes.html 208 - Section Overview.srt 220 - Optional Reloading Colab Notebook.mp4 211 - Introduction to Google Colab example notebook.txt 228 - Yann LeCuns OG of deep learning Tweet on Batch Sizes.txt 210 - Setting Up With Google.html 239 - Training Your Deep Neural Network.srt 236 - Summarizing Our Model.mp4 217 - Loading TensorFlow 20 into a Colab Notebook if it isnt the default.txt 215 - Setting Up Our Data 2.srt 226 - Preprocess Images 2.mp4 211 - Setting Up Google Colab.srt 216 - Importing TensorFlow 2.srt 230 - Preparing Our Inputs and Outputs.mp4 211 - Google Colab our workspace for the upcoming project.txt 221 - Loading Our Data Labels.mp4 242 - TensorFlow documentation for the unbatch function.txt 234 - Building A Deep Learning Model 3.srt 245 - Visualizing And Evaluate Model Predictions 3.srt 250 - Making Predictions On Our Images.mp4 235 - Building A Deep Learning Model 4.mp4 225 - Preprocess Images.srt 219 - Introduction to Google Colab example notebook.txt 232 - TensorFlow Hub resource for pretrained deep learning models and more.txt 220 - Optional Reloading Colab Notebook.srt 217 - Optional TensorFlow 20 Default Issue.mp4 211 - Endtoend Dog Vision Notebook the project well be working through.txt 211 - Google Colab IO example how to get data in and out of your Colab notebook.txt 241 - Make And Transform Predictions.mp4 250 - Making Predictions On Our Images.srt 222 - Preparing The Images.mp4 218 - Using A GPU.srt 212 - Google Colab FAQ things you should know about Google Colab.txt 219 - Optional GPU and Google Colab.mp4 249 - Dog Vision Predictions with MobileNetV2 Ready for Kaggle Submission.txt 227 - Turning Data Into Batches.mp4 230 - TensorFlow Hub resource for pretrained deep learning models and more.txt 242 - Transform Predictions To Text.mp4 248 - Dog Vision Prediction Probabilities Array.txt 213 - Google Colab IO example how to get data in and out of your Colab notebook.txt 214 - Setting Up Our Data.srt 241 - Make And Transform Predictions.srt 211 - Setting Up Google Colab.mp4 222 - Preparing The Images.srt 233 - Building A Deep Learning Model 2.mp4 212 - Google Colab Workspace.mp4 250 - Endtoend Dog Vision Notebook from the videos.txt 239 - Training Your Deep Neural Network.mp4 211 - Kaggle Dog Breed Identification Competition the basis of our upcoming project.txt 249 - Submitting Model to Kaggle.mp4 234 - MobileNetV2 the model were using architecture explanation by SikHo Tsang.txt 228 - Turning Data Into Batches 2.mp4 247 - Training Model On Full Dataset.srt 248 - Making Predictions On Test Images.srt 232 - Papers with Code a great resource for .txt 236 - Summarizing Our Model.srt 214 - Setting Up Our Data.mp4 240 - Evaluating Performance With TensorBoard.srt 224 - Creating Our Own Validation Set.srt 229 - Visualizing Our Data.srt 251 - Finishing Dog Vision Where to next.html 238 - Preventing Overfitting.mp4 225 - Preprocess Images.mp4 213 - Uploading Project Data.mp4 245 - Visualizing And Evaluate Model Predictions 3.mp4 223 - Turning Data Labels Into Numbers.mp4 244 - Visualizing And Evaluate Model Predictions 2.srt 224 - Creating Our Own Validation Set.mp4 228 - Turning Data Into Batches 2.srt 209 - Deep Learning and Unstructured Data.srt 208 - Section Overview.mp4 232 - MobileNetV2 the model were using on TensorFlow Hub.txt 215 - Setting Up Our Data 2.mp4 237 - Evaluating Our Model.mp4 246 - Saving And Loading A Trained Model.mp4 238 - Preventing Overfitting.srt 218 - Using A GPU.mp4 242 - Transform Predictions To Text.srt 223 - Turning Data Labels Into Numbers.srt 216 - Importing TensorFlow 2.mp4 238 - Early Stopping Callback a way to stop your model from training when it stops .txt 218 - Google Colab example GPU usage.txt 209 - Deep Learning and Unstructured Data.mp4 213 - Kaggle Dog Breed Identification Competition Data.txt 219 - Optional GPU and Google Colab.srt 243 - Visualizing Model Predictions.srt 225 - TensorFlow guidelines for loading all kinds of data turning your data into Tensors.txt 232 - PyTorch Hub PyTorch version of TensorFlow Hub.txt 230 - Preparing Our Inputs and Outputs.srt 237 - TensorBoard Callback Documentation.txt 219 - Google Colab Example of GPU speed up versus CPU.txt 237 - Evaluating Our Model.srt 233 - Keras in TensorFlow Overview Documentation.txt 232 - Building A Deep Learning Model.mp4 226 - Preprocess Images 2.srt 225 - Documentation for loading images in TensorFlow.txt 233 - Building A Deep Learning Model 2.srt 229 - Visualizing Our Data.mp4 249 - Submitting Model to Kaggle.srt 232 - Building A Deep Learning Model.srt 201 - OLTP vs OLAP.txt 198 - What Is A Data Engineer 2.mp4 199 - What Is A Data Engineer 3.srt 207 - Kafka and Stream Processing.srt 199 - What Is A Data Engineer 3.mp4 196 - Kaggle.txt 204 - Optional Learn SQL.html 195 - Data Engineering Introduction.srt 205 - Hadoop HDFS and MapReduce.mp4 207 - Kafka and Stream Processing.mp4 206 - Apache Spark and Apache Flink.mp4 205 - Hadoop HDFS and MapReduce.srt 201 - Types Of Databases.srt 201 - A Primer on ACID Transactions.txt 200 - What Is A Data Engineer 4.srt 202 - Quick Note Upcoming Video.html 198 - What Is A Data Engineer 2.srt 203 - Optional OLTP Databases.srt 206 - Apache Spark and Apache Flink.srt 201 - Types Of Databases.mp4 197 - What Is A Data Engineer.mp4 196 - What Is Data.mp4 195 - Data Engineering Introduction.mp4 203 - Optional OLTP Databases.mp4 197 - What Is A Data Engineer.srt 200 - What Is A Data Engineer 4.mp4 196 - What Is Data.srt 7 - Teachable Machine.txt 9 - Machine Learning Playground.txt 5 - What Is Machine Learning.mp4 6 - AIMachine LearningData Science.mp4 8 - How Did We Get Here.srt 10 - Types of Machine Learning.srt 13 - Section Review.srt 12 - What Is Machine Learning Round 2.srt 10 - Types of Machine Learning.mp4 9 - Exercise YouTube Recommendation Engine.mp4 14 - Monthly Coding Challenges Free Resources and Guides.html 12 - What Is Machine Learning Round 2.mp4 13 - Section Review.mp4 9 - Exercise YouTube Recommendation Engine.srt 6 - AIMachine LearningData Science.srt 11 - Are You Getting It Yet.html 5 - What Is Machine Learning.srt 7 - Exercise Machine Learning Playground.mp4 8 - How Did We Get Here.mp4 7 - Exercise Machine Learning Playground.srt 36 - Conda Environments.mp4 44 - Jupyter Notebook Walkthrough 2.srt 35 - conda-cheatsheet.pdf 38 - Mac Environment Setup 2.srt 43 - heart-disease.csv 34 - Introducing Our Tools.srt 43 - 6-step-ml-framework.png 36 - Conda Environments.srt 37 - Mac Environment Setup.srt 41 - Linux Environment Setup.html 43 - Dataquest Jupyter Notebook for Beginners Tutorial.txt 45 - Jupyter Notebook Walkthrough 3.mp4 38 - Mac Environment Setup 2.mp4 33 - Section Overview.srt 45 - Jupyter Notebook Walkthrough 3.srt 37 - Miniconda download documentation.txt 40 - Windows Environment Setup 2.srt 40 - Windows Environment Setup 2.mp4 35 - Getting your computer ready for machine learning How what and why you should use Anaconda Miniconda and Conda blog post.txt 39 - Windows Environment Setup.srt 37 - Mac Environment Setup.mp4 43 - Jupyter Notebook Walkthrough.mp4 39 - Miniconda download documentation.txt 39 - Windows Environment Setup.mp4 43 - Jupyter Notebook documentation.txt 35 - What is Conda.mp4 42 - Conda documentation on sharing an environment.txt 43 - Jupyter Notebook Walkthrough.srt 35 - Conda documentation.txt 33 - Section Overview.mp4 35 - Getting started with Conda documentation.txt 35 - What is Conda.srt 44 - Jupyter Notebook Walkthrough 2.mp4 42 - Sharing your Conda Environment.html 285 - Math Functions.srt 284 - Floating point numbers.txt 300 - String Methods.txt 276 - Replit.txt 321 - Sets.srt 298 - Exercise Repl.txt 302 - Exercise Type Conversion.srt 292 - Augmented Assignment Operator.srt 287 - Operator Precedence.srt 300 - Built in Functions.txt 297 - Exercise Repl.txt 303 - DEVELOPER FUNDAMENTALS II.srt 318 - Dictionary Methods 2.srt 298 - String Indexes.mp4 306 - List Slicing.mp4 298 - String Indexes.srt 317 - Dictionary Methods.srt 306 - Exercise Repl.txt 279 - Python 2 vs Python 3.txt 308 - List Methods.mp4 316 - Dictionary Keys.mp4 295 - Type Conversion.mp4 322 - Exercise Repl.txt 311 - Common List Patterns.mp4 302 - Exercise Type Conversion.mp4 306 - List Slicing.srt 308 - List Methods.srt 286 - DEVELOPER FUNDAMENTALS I.mp4 309 - List Methods 2.mp4 277 - Our First Python Program.mp4 318 - Exercise Repl.txt 307 - Matrix.srt 307 - Matrix.mp4 304 - Exercise Password Checker.srt 281 - Learning Python.mp4 307 - Exercise Repl.txt 310 - List Methods 3.mp4 289 - Optional bin and complex.srt 297 - Formatted Strings.mp4 279 - Python 2 vs Python 3 another one.txt 319 - Tuples.srt 290 - Python Keywords.txt 277 - Our First Python Program.srt 287 - Operator Precedence.mp4 288 - Exercise Repl.txt 279 - The Story of Python.txt 284 - Numbers.srt 299 - Immutability.srt 295 - Type Conversion.srt 322 - Sets Methods.txt 317 - Dictionary Methods.txt 310 - List Methods 3.srt 301 - Booleans.mp4 314 - Dictionaries.srt 281 - Learning Python.srt 318 - Dictionary Methods 2.mp4 313 - None.mp4 300 - BuiltIn Functions Methods.mp4 311 - Exercise Repl.txt 280 - Exercise How Does Python Work.mp4 300 - BuiltIn Functions Methods.srt 308 - List Methods.txt 287 - Exercise Repl.txt 284 - Numbers.mp4 304 - Exercise Password Checker.mp4 290 - Variables.srt 311 - Common List Patterns.srt 274 - What Is A Programming Language.srt 317 - Dictionary Methods.mp4 276 - How To Run Python Code.srt 312 - List Unpacking.mp4 297 - 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Dictionary Keys.srt 319 - Tuples.mp4 322 - Sets 2.mp4 314 - Dictionaries.mp4 283 - How To Succeed.html 322 - Sets 2.srt 293 - Strings.mp4 320 - Tuple Methods.txt 275 - pythonorg.txt 278 - Latest Version Of Python.srt 309 - Python Keywords.txt 292 - Exercise Repl.txt 279 - Python 2 vs Python 3.srt 301 - Booleans.srt 320 - Tuples 2.srt 291 - Expressions vs Statements.mp4 257 - Communicating With Outside World.srt 254 - Communicating With Managers.mp4 252 - Section Overview.srt 255 - Communicating With CoWorkers.mp4 257 - Communicating With Outside World.mp4 258 - Storytelling.mp4 253 - Communicating Your Work.mp4 253 - Communicating Your Work.srt 255 - Communicating With CoWorkers.srt 253 - How to Think About Communicating and Sharing Your Work blog post.txt 257 - Devblog by Hashnode an easy and free way to create a blog you own.txt 258 - Storytelling.srt 259 - Communicating and sharing your work Further reading.html 254 - Communicating With Managers.srt 256 - Weekend Project Principle.mp4 256 - 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