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【影视】 [FreeCoursesOnline.Me] [Stone River eLearning] Math for Machine Learning - [FCO]

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16.LDA Example 2.mp4 28.2 MB
67.Support Vector Classifier Example 1.mp4 23.1 MB
22.Maximizing the Log-Likelihood Function.mp4 22.5 MB
15.LDA Example 1.mp4 21.1 MB
26.Neural Network Model of the Output Functions.mp4 19.7 MB
05.Linear Algebra Solution to Least Squares Problem.mp4 18.8 MB
04.The Least Squares Method.mp4 18.4 MB
55.Maximal Margin Classifier Example 2.mp4 17.5 MB
21.The Multivariate Newton-Raphson Method.mp4 17.4 MB
54.Maximal Margin Classifier Example 1.mp4 15.1 MB
68.Support Vector Classifier Example 2.mp4 15.0 MB
23.Logistic Regression Example.mp4 15.0 MB
45.Proof 4.mp4 13.6 MB
20.Estimating the Posterior Probability Function.mp4 13.5 MB
42.Reformulating the Optimization Problem.mp4 12.8 MB
11.Modelling the Posterior Probability Functions.mp4 11.9 MB
03.Linear Regression.mp4 11.5 MB
39.Proof 1.mp4 11.4 MB
63.Solving the Convex Optimization Problem (Soft Margin).mp4 9.9 MB
33.Minimizing the Error Function Using Gradient Descent.mp4 9.7 MB

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【影视】 [ FreeCourseWeb.com ] Linkedin - Build a Personal Learning Plan and Stick with It

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~Get Your Files Here !/[1] Introduction/[1] Why do you need a personal learning plan.mp4 38.3 MB
~Get Your Files Here !/[3] 2. Determine Required Skills/[2] Solicit feedback.mp4 37.3 MB
~Get Your Files Here !/[6] 5. Stick with Your Learning Plan/[3] Celebrate your progress.mp4 36.9 MB
~Get Your Files Here !/[4] 3. Identify Your Learning Preference/[2] Social learning.mp4 36.8 MB
~Get Your Files Here !/[6] 5. Stick with Your Learning Plan/[1] Identify and build a support network.mp4 36.7 MB
~Get Your Files Here !/[2] 1. Define Your Objectives and Motivations/[1] Define your end goal and your why.mp4 36.2 MB
~Get Your Files Here !/[3] 2. Determine Required Skills/[3] Prioritize the skills you need to build.mp4 34.1 MB
~Get Your Files Here !/[5] 4. Create Your Learning Action Plan/[1] Establish SMART goals.mp4 33.1 MB
~Get Your Files Here !/[3] 2. Determine Required Skills/[1] Perform a skills self-assessment.mp4 30.2 MB
~Get Your Files Here !/[4] 3. Identify Your Learning Preference/[3] Experiential learning.mp4 30.1 MB
~Get Your Files Here !/[4] 3. Identify Your Learning Preference/[1] Formal learning.mp4 25.5 MB
~Get Your Files Here !/[5] 4. Create Your Learning Action Plan/[2] Identify learning resources.mp4 25.2 MB
~Get Your Files Here !/[6] 5. Stick with Your Learning Plan/[2] Create personal accountability.mp4 25.1 MB
~Get Your Files Here !/[7] Conclusion/[1] Learning is a journey.mp4 15.4 MB
~Get Your Files Here !/Ex_Files_Personal_Learning_Plan/Exercise Files/Learning Plan Framework.pdf 81.6 kB
~Get Your Files Here !/[3] 2. Determine Required Skills/[2] Solicit feedback.srt 8.9 kB
~Get Your Files Here !/[6] 5. Stick with Your Learning Plan/[1] Identify and build a support network.srt 8.4 kB
~Get Your Files Here !/[5] 4. Create Your Learning Action Plan/[1] Establish SMART goals.srt 8.4 kB
~Get Your Files Here !/[3] 2. Determine Required Skills/[3] Prioritize the skills you need to build.srt 8.4 kB
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【影视】 LinkedIn Learning - Data Science Foundations Fundamentals [CoursesGhar]

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[3] 2. The Place of Data Science in the Data Universe/[3] Deep learning neural networks.mp4 32.0 MB
[3] 2. The Place of Data Science in the Data Universe/[2] Machine learning.mp4 31.4 MB
[5] 4. Sources of Data/[5] Scraping data.mp4 31.2 MB
[3] 2. The Place of Data Science in the Data Universe/[1] Artificial intelligence.mp4 31.0 MB
[9] 8. Analyses for Data Science/[2] Predictive models.mp4 25.7 MB
[6] 5. Sources of Rules/[2] The derivation of rules from data analysis.mp4 25.0 MB
[2] 1. What Is Data Science/[3] The data science pathway.mp4 24.4 MB
[9] 8. Analyses for Data Science/[1] Descriptive analyses.mp4 24.3 MB
[5] 4. Sources of Data/[3] Open data.mp4 21.5 MB
[9] 8. Analyses for Data Science/[7] Dimensionality reduction.mp4 20.4 MB
[9] 8. Analyses for Data Science/[3] Trend analysis.mp4 20.1 MB
[9] 8. Analyses for Data Science/[4] Clustering.mp4 19.3 MB
[9] 8. Analyses for Data Science/[9] Validating models.mp4 19.1 MB
[9] 8. Analyses for Data Science/[6] Anomaly detection.mp4 19.1 MB
[9] 8. Analyses for Data Science/[8] Feature selection and creation.mp4 17.7 MB
[7] 6. Tools for Data Science/[1] Applications for data analysis.mp4 15.9 MB
[9] 8. Analyses for Data Science/[10] Aggregating models.mp4 15.8 MB
[5] 4. Sources of Data/[1] Data preparation.mp4 15.7 MB
[3] 2. The Place of Data Science in the Data Universe/[4] Big data.mp4 15.6 MB
[8] 7. Mathematics for Data Science/[1] Algebra.mp4 15.6 MB

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【其他】 [ FreeCourseWeb.com ] Linkedin - Power BI - Integrating AI and Machine Learning

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~Get Your Files Here !/[4] 3. Measuring Relationships between Variables/[6] Calculating best fit line.mp4 33.2 MB
~Get Your Files Here !/[6] 5. Analyzing Time Series Data/[6] Analyzing predictions vs. actuals.mp4 25.4 MB
~Get Your Files Here !/[6] 5. Analyzing Time Series Data/[3] Leveraging anomaly detection.mp4 24.1 MB
~Get Your Files Here !/[4] 3. Measuring Relationships between Variables/[4] Visualizing correlations.mp4 22.8 MB
~Get Your Files Here !/[3] 2. Analyzing a Single Variable/[5] Calculating rolling averages.mp4 21.7 MB
~Get Your Files Here !/[4] 3. Measuring Relationships between Variables/[3] Calculating correlations.mp4 20.6 MB
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【影视】 [FreeCourseSite.com] Udemy - Complete 2022 Data Science & Machine Learning Bootcamp

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04. Introduction to Optimisation and the Gradient Descent Algorithm/08. [Python] - Advanced Functions and the Pitfalls of Optimisation (Part 1).mp4 305.5 MB
04. Introduction to Optimisation and the Gradient Descent Algorithm/06. [Python] - Loops and the Gradient Descent Algorithm.mp4 301.4 MB
10. Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/12. Model Evaluation and the Confusion Matrix.mp4 264.1 MB
05. Predict House Prices with Multivariable Linear Regression/32. Build a Valuation Tool (Part 3) Docstrings & Creating your own Python Module.mp4 256.0 MB
04. Introduction to Optimisation and the Gradient Descent Algorithm/10. Understanding the Learning Rate.mp4 248.1 MB
12. Serving a Tensorflow Model through a Website/12. Introduction to OpenCV.mp4 246.8 MB
03. Python Programming for Data Science and Machine Learning/10. [Python] - Module Imports.mp4 243.3 MB
12. Serving a Tensorflow Model through a Website/14. Calculating the Centre of Mass and Shifting the Image.mp4 234.1 MB
04. Introduction to Optimisation and the Gradient Descent Algorithm/09. [Python] - Tuples and the Pitfalls of Optimisation (Part 2).mp4 229.6 MB
10. Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/10. Use the Model to Make Predictions.mp4 228.9 MB
05. Predict House Prices with Multivariable Linear Regression/14. Working with Seaborn Pairplots & Jupyter Microbenchmarking Techniques.mp4 224.8 MB
11. Use Tensorflow to Classify Handwritten Digits/12. Different Model Architectures Experimenting with Dropout.mp4 224.1 MB
08. Test and Evaluate a Naive Bayes Classifier Part 3/06. Visualising the Decision Boundary.mp4 215.3 MB
08. Test and Evaluate a Naive Bayes Classifier Part 3/11. A Naive Bayes Implementation using SciKit Learn.mp4 204.6 MB
04. Introduction to Optimisation and the Gradient Descent Algorithm/11. How to Create 3-Dimensional Charts.mp4 202.9 MB
10. Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/09. Use Regularisation to Prevent Overfitting Early Stopping & Dropout Techniques.mp4 200.8 MB
12. Serving a Tensorflow Model through a Website/07. Loading a Tensorflow.js Model and Starting your own Server.mp4 197.2 MB
12. Serving a Tensorflow Model through a Website/09. Styling an HTML Canvas.mp4 196.5 MB
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learning-patterns-final-v1.1_hocr.html 9.3 MB
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【影视】 Udemy - The Memory Improvement And Learning MasterClass For Success (AKUMA)

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~Get Your Course Here !/1. The Superhuman Memory - Epigenetic and Habitual Memory Systems/1. The Human Memory - How Does It Work--- [ FreeCourseWeb.com ] ---.mp4 153.1 MB
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23 Hierarchical Clustering/004 Hierarchical Clustering - Coding Part Two - Scikit-Learn.mp4 218.8 MB
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13 Logistic Regression/016 Logistic Regression Project Exercise - Solutions.mp4 152.6 MB
08 Data Analysis and Visualization Capstone Project Exercise/004 Capstone Project Solutions - Part Three.mp4 143.9 MB
17 Random Forests/007 Coding Classification with Random Forest Classifier - Part Two.mp4 136.7 MB
05 Pandas/026 Pandas Pivot Tables.mp4 135.0 MB
24 DBSCAN - Density-based spatial clustering of applications with noise/007 DBSCAN - Outlier Project Exercise Solutions.mp4 134.2 MB
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11 Feature Engineering and Data Preparation/005 Dealing with Missing Data _ Part Two - Filling or Dropping data based on Rows.mp4 123.3 MB
16 Tree Based Methods_ Decision Tree Learning/008 Coding Decision Trees - Part Two -Creating the Model.mp4 121.5 MB
23 Hierarchical Clustering/003 Hierarchical Clustering - Coding Part One - Data and Visualization.mp4 120.4 MB
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24 DBSCAN - Density-based spatial clustering of applications with noise/002 DBSCAN - Theory and Intuition.mp4 114.4 MB
20 Naive Bayes Classification and Natural Language Processing (Supervised Learning)/010 Text Classification Project Exercise Solutions.mp4 113.3 MB
22 K-Means Clustering/011 K-Means Clustering Exercise Solution - Part Two.mp4 113.1 MB
08 Data Analysis and Visualization Capstone Project Exercise/003 Capstone Project Solutions - Part Two.mp4 111.4 MB
06 Matplotlib/011 Matplotlib Exercise Questions - Solutions.mp4 111.0 MB
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11 Feature Engineering and Data Preparation/006 Dealing with Missing Data _ Part 3 - Fixing data based on Columns.mp4 110.4 MB
24 DBSCAN - Density-based spatial clustering of applications with noise/005 DBSCAN - Hyperparameter Tuning Methods.mp4 110.2 MB

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