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9. Appendix 1 Excel crash course/7. Formatting data and tables.mp4 167.0 MB
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7. Handling Changing Trend & Seasonality over time/2. Excel Winter's method.mp4 132.9 MB
6. Identifying Seasonality & Trend for Forecasting/6. Excel Moving Average Method.mp4 125.6 MB
5. Handling Special events like Holiday sales/2. Excel Running Linear Regression using Solver.mp4 117.1 MB
9. Appendix 1 Excel crash course/1. Mathematical Formulas.mp4 114.8 MB
9. Appendix 1 Excel crash course/2. Textual Formulas.mp4 114.4 MB
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6. Identifying Seasonality & Trend for Forecasting/2. Excel Additive model to identify Trend & Seasonality.mp4 94.0 MB
3. Getting Data Ready for Regression Model/13. Correlation Analysis.mp4 84.0 MB
2. Basics of Forecasting/3. Creating Linear Model with Trendlines.mp4 82.8 MB
3. Getting Data Ready for Regression Model/3. The Data and the Data Dictionary.mp4 82.4 MB
9. Appendix 1 Excel crash course/3. Logical Formulas.mp4 81.5 MB
9. Appendix 1 Excel crash course/8. Pivot Tables.mp4 76.7 MB

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10. Appendix/2. Windows-Focused Environment Setup 2018.mp4 195.4 MB
10. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
4. Hidden Markov Models for Discrete Observations/11. Discrete HMM in Code.mp4 49.7 MB
6. HMMs for Continuous Observations/3. Continuous-Observation HMM in Code (part 1).mp4 49.0 MB
6. HMMs for Continuous Observations/5. Continuous HMM in Theano.mp4 47.6 MB
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5. Discrete HMMs Using Deep Learning Libraries/3. Discrete HMM in Theano.mp4 32.2 MB
10. Appendix/10. What order should I take your courses in (part 1).mp4 30.8 MB
4. Hidden Markov Models for Discrete Observations/13. Discrete HMM Updates in Code with Scaling.mp4 30.6 MB
3. Markov Models Example Problems and Applications/4. Example Application Build a 2nd-order language model and generate phrases.mp4 28.2 MB
5. Discrete HMMs Using Deep Learning Libraries/4. Improving our Gradient Descent-Based HMM.mp4 27.2 MB
10. Appendix/4. How to Code by Yourself (part 1).mp4 25.7 MB
7. HMMs for Classification/2. HMM Classification on Poetry Data (Robert Frost vs. Edgar Allan Poe).mp4 25.6 MB
5. Discrete HMMs Using Deep Learning Libraries/2. Theano Scan Tutorial.mp4 24.9 MB
5. Discrete HMMs Using Deep Learning Libraries/5. Tensorflow Scan Tutorial.mp4 24.2 MB
5. Discrete HMMs Using Deep Learning Libraries/1. Gradient Descent Tutorial.mp4 23.9 MB
6. HMMs for Continuous Observations/6. Continuous HMM in Tensorflow.mp4 23.6 MB
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[ FreeCourseWeb.com ] Oreilly - Deploying TensorFlow Models to a Web Application - Using Flask API, TensorFlowJS, and TensorFlow Serving.zip

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[DesireCourse.Com] Udemy - Deployment of Machine Learning Models

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2. Machine Learning Pipeline - Research Environment/6. Data Analysis - Demo.mp4 142.0 MB
2. Machine Learning Pipeline - Research Environment/7. Feature Engineering - Demo.mp4 102.9 MB
13. A Deep Learning Model with Big Data/3. Building a CNN in the Research Environment.mp4 93.1 MB
4. Building a Reproducible Machine Learning Pipeline/2. Procedural Programming Pipeline.mp4 90.4 MB
4. Building a Reproducible Machine Learning Pipeline/5. Third Party Pipeline Create Scikit-Learn compatible Feature Transformers.mp4 88.4 MB
13. A Deep Learning Model with Big Data/4. Production Code for a CNN Learning Pipeline.mp4 83.4 MB
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6. Creating a Machine Learning Pipeline Application/8. 6.7 - Versioning and Logging.mp4 73.9 MB
8. Continuous Integration and Deployment Pipelines/4. 8.4 - Publishing the Model to Gemfury.mp4 72.5 MB
2. Machine Learning Pipeline - Research Environment/10. Getting Ready for Deployment - Demo.mp4 71.1 MB
2. Machine Learning Pipeline - Research Environment/1. Machine Learning Pipeline Overview.mp4 63.5 MB
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2. Machine Learning Pipeline - Research Environment/2. Machine Learning Pipeline Feature Engineering.mp4 60.5 MB
4. Building a Reproducible Machine Learning Pipeline/4. Leveraging a Third Party Pipeline Scikit-Learn.mp4 59.4 MB
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