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
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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
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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 - Formatted Strings.srt
274 - What Is A Programming Language.mp4
278 - Latest Version Of Python.mp4
279 - Python 2 vs Python 3.mp4
313 - None.srt
275 - Python Interpreter.mp4
291 - Expressions vs Statements.srt
285 - Math Functions.mp4
315 - DEVELOPER FUNDAMENTALS III.srt
289 - Base Numbers.txt
288 - Exercise Operator Precedence.html
294 - String Concatenation.srt
294 - String Concatenation.mp4
315 - DEVELOPER FUNDAMENTALS III.mp4
303 - DEVELOPER FUNDAMENTALS II.mp4
282 - Python Data Types.srt
312 - List Unpacking.srt
276 - Glotio.txt
290 - Variables.mp4
299 - Immutability.mp4
289 - Optional bin and complex.mp4
292 - Augmented Assignment Operator.mp4
282 - Python Data Types.mp4
305 - Lists.srt
296 - Escape Sequences.mp4
293 - Strings.srt
303 - Python Comments Best Practices.txt
309 - Exercise Repl.txt
276 - How To Run Python Code.mp4
309 - List Methods 2.srt
280 - Exercise How Does Python Work.srt
296 - Escape Sequences.srt
305 - Lists.mp4
320 - Tuples 2.mp4
321 - Sets.mp4
275 - Python Interpreter.srt
316 - 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 - Weekend Project Principle.srt
252 - Section Overview.mp4
257 - fasttemplate by fastai a template you can use for your blog on GitHub Pages.txt
28 - Tools We Will Use.srt
15 - Section Overview.mp4
19 - Types of Data.srt
18 - Types of Machine Learning Problems.srt
28 - Tools We Will Use.mp4
19 - Types of Data.mp4
18 - Types of Machine Learning Problems.mp4
27 - Experimentation.srt
24 - Modelling Tuning.mp4
23 - Modelling Picking the Model.srt
20 - Types of Evaluation.mp4
27 - Experimentation.mp4
15 - Section Overview.srt
25 - Modelling Comparison.srt
25 - Modelling Comparison.mp4
17 - A 6 Step Field Guide for Machine Learning Modelling blog post.txt
21 - Features In Data.mp4
22 - Modelling Splitting Data.srt
29 - Optional Elements of AI.html
23 - Modelling Picking the Model.mp4
22 - Modelling Splitting Data.mp4
16 - Introducing Our Framework.mp4
24 - Modelling Tuning.srt
21 - Features In Data.srt
17 - 6 Step Machine Learning Framework.mp4
26 - Overfitting and Underfitting Definitions.html
20 - Types of Evaluation.srt
16 - Introducing Our Framework.srt
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