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【影视】 [DesireCourse.Net] Udemy - Convolutional Neural Networks Mastery - Deep Learning - CNN

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3. AutoGrad in Pytorch/1. Autograd in Pytorch.mp4 144.2 MB
4. Creating Deep Neural Networks in Pytorch/1. Building first neural network.mp4 101.7 MB
5. CNN on Pytorch/3. CNN Recap.mp4 76.9 MB
2. Introduction/1. Getting System Ready.mp4 66.3 MB
5. CNN on Pytorch/1. Data Loading - CIFAR10.mp4 61.5 MB
6. LeNet Architecture in Pytorch/2. LeNet Model in Pytorch.mp4 55.0 MB
7. Bonus Access/2. Linear Algebra for Data Science.mp4 49.2 MB
7. Bonus Access/3. Deep Learning Calculus.mp4 44.2 MB
6. LeNet Architecture in Pytorch/3. Preparation & Evaluation.mp4 44.1 MB
6. LeNet Architecture in Pytorch/1. LeNet Overview.mp4 43.0 MB
7. Bonus Access/4. Deep Learning from Scratch using Tensorflow - Keras.mp4 39.9 MB
2. Introduction/7. Pytorch on GPU.mp4 39.2 MB
5. CNN on Pytorch/4. First CNN.mp4 33.5 MB
5. CNN on Pytorch/5. CNN Deep layers.mp4 32.7 MB
2. Introduction/2. Create Tensors in Pytorch.mp4 31.1 MB
3. AutoGrad in Pytorch/2. Implementing Gradient Descent using Autograd.mp4 30.1 MB
4. Creating Deep Neural Networks in Pytorch/3. Writing Custom NN module.mp4 26.7 MB
2. Introduction/5. Numpy in Pytorch.mp4 24.7 MB
2. Introduction/6. What is CUDA.mp4 18.2 MB
1. Welcome Aboard/1. Why PyTorch is Powerful.mp4 17.8 MB

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【影视】 [Tutorialsplanet.NET] Udemy - Learning Python for Data Analysis and Visualization

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10. Machine Learning/16. Decision Trees and Random Forests.mp4 160.4 MB
10. Machine Learning/9. Logistic Regression Part 4.mp4 102.7 MB
9. Example Projects/12. Data Project - Stock Market Analysis Part 5.mp4 98.5 MB
10. Machine Learning/19. Natural Language Processing Part 3.mp4 97.0 MB
10. Machine Learning/13. Support Vector Machines - Part 2.mp4 90.0 MB
9. Example Projects/17. Data Project - Election Analysis Part 4.mp4 86.1 MB
11. Appendix Statistics Overview/9. Hypothesis Testing and Confidence Intervals.mp4 82.7 MB
10. Machine Learning/5. Linear Regression Part 4.mp4 82.5 MB
10. Machine Learning/11. Multi Class Classification Part 2 - k Nearest Neighbor.mp4 77.1 MB
10. Machine Learning/6. Logistic Regression Part 1.mp4 75.3 MB
10. Machine Learning/4. Linear Regression Part 3.mp4 72.2 MB
10. Machine Learning/10. Multi Class Classification Part 1 - Logistic Regression.mp4 71.1 MB
10. Machine Learning/20. Natural Language Processing Part 4.mp4 70.4 MB
10. Machine Learning/15. Naive Bayes Part 2.mp4 68.7 MB
10. Machine Learning/12. Support Vector Machines Part 1.mp4 68.1 MB
8. Data Visualization/3. Kernel Density Estimate Plots.mp4 64.9 MB
10. Machine Learning/18. Natural Language Processing Part 2.mp4 62.6 MB
10. Machine Learning/2. Linear Regression Part 1.mp4 61.5 MB
9. Example Projects/9. Data Project - Stock Market Analysis Part 2.mp4 59.6 MB
9. Example Projects/15. Data Project - Election Analysis Part 2.mp4 59.1 MB

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【影视】 [DesireCourse.Net] Udemy - Master Deep Learning with TensorFlow in Python

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14. Appendix Linear Algebra Fundamentals/11. Why is Linear Algebra Useful.mp4 151.3 MB
1. Welcome! Course introduction/1. Meet your instructors and why you should study machine learning.mp4 110.9 MB
14. Appendix Linear Algebra Fundamentals/3. Linear Algebra and Geometry.mp4 52.2 MB
14. Appendix Linear Algebra Fundamentals/10. Dot Product of Matrices.mp4 51.8 MB
2. Introduction to neural networks/24. N-parameter gradient descent.mp4 41.4 MB
2. Introduction to neural networks/12. The linear model. Multiple inputs and multiple outputs.mp4 40.1 MB
14. Appendix Linear Algebra Fundamentals/8. Transpose of a Matrix.mp4 39.9 MB
13. Business case/4. Preprocessing the data.mp4 36.0 MB
14. Appendix Linear Algebra Fundamentals/2. Scalars and Vectors.mp4 35.5 MB
14. Appendix Linear Algebra Fundamentals/1. What is a Matrix.mp4 35.2 MB
14. Appendix Linear Algebra Fundamentals/6. Addition and Subtraction of Matrices.mp4 34.2 MB
13. Business case/6. Create a class for batching.mp4 29.0 MB
14. Appendix Linear Algebra Fundamentals/4. Scalars, Vectors and Matrices in Python.mp4 28.0 MB
14. Appendix Linear Algebra Fundamentals/9. Dot Product of Vectors.mp4 25.2 MB
13. Business case/1. Exploring the dataset and identifying predictors.mp4 24.4 MB
14. Appendix Linear Algebra Fundamentals/5. Tensors.mp4 23.6 MB
12. The MNIST example/9. Discuss the results and test.mp4 23.0 MB
4. Minimal example - your first machine learning algorithm/4. Minimal example - part 4.mp4 21.8 MB
13. Business case/7. Outlining the model.mp4 20.4 MB
12. The MNIST example/4. Outlining the model.mp4 19.3 MB

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【影视】 [ CourseBoat.com ] Udemy - Automated Machine Learning Hands on AutoML for beginners

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【影视】 Class101 - Inhyuk Lee - Advancing to Intermediate Illustration - Steps after Learning Basics

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1 Preparing to Draw/1 - 그림을 그리기위한 마인드 세팅 .mp4 397.4 MB
9 Coloring/4 - [Bonus] 입체화된 캐릭터의 색변환 기초 .mp4 388.7 MB
4 Applying Muscles Using Geometric Figure Drawing 2/1 - 다양한 포즈 스케치 - 실사 레퍼런스의 이해와 훈련법 (1) .mp4 383.4 MB
10 Completion/6 - 레이어를 활용한 색 더하기와 디테일 추가 (1) .mp4 381.5 MB
10 Completion/9 - 포토샵 필터를 활용한 마무리 작업 (2) .mp4 332.2 MB
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8 Clothing/3 - 기본의상 변형하기.mp4 325.4 MB
11 Congratulations on Completing the Course/1 - 완강을 축하드립니다..mp4 324.2 MB
10 Completion/2 - 채색을 활용한 전신 입체화 (2) .mp4 318.4 MB
10 Completion/5 - 캐릭터 전신 마감처리 (2) .mp4 315.4 MB
6 Hands and Feet/8 - 발 형태의 변형.mp4 307.2 MB
6 Hands and Feet/12 - 신발과 장갑의 입체화 .mp4 300.4 MB
2 Drawing Body Muscles Using Geometric Figure Drawing/3 - 인체근육 스케치 - 측면&후면 .mp4 292.1 MB
10 Completion/1 - 채색을 활용한 전신 입체화 (1) .mp4 285.5 MB
10 Completion/8 - 포토샵 필터를 활용한 마무리 작업 (1) .mp4 275.8 MB
1 Preparing to Draw/3 - 초급강의 프리챕터 참가자 인체도형 피드백 .mp4 275.1 MB
8 Clothing/2 - 기본의상 스케치&입체화 .mp4 267.4 MB
1 Preparing to Draw/4 - 포토샵 기본 도구 숙지 - 브러쉬, 필압, 단축키, 툴, 레이어 등.mp4 261.6 MB

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【影视】 [ DevCourseWeb.com ] Udemy - Python for Machine Learning Project based Master course

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~Get Your Files Here !/02 - Python Salary Predictor Project/010 Contribution to Data (Primary Data as .CSV).mp4 142.6 MB
~Get Your Files Here !/03 - Machine learning Classifier project/005 Streamlit Classifiers and dealing with Errors.mp4 109.4 MB
~Get Your Files Here !/05 - Challenge (Create a BMI calculator)/002 BMI Calculator video (Explanation of the code).mp4 107.2 MB
~Get Your Files Here !/02 - Python Salary Predictor Project/008 Prediction using Linear progression on Plots.mp4 98.3 MB
~Get Your Files Here !/03 - Machine learning Classifier project/004 Select Dataset and Keys.mp4 73.6 MB
~Get Your Files Here !/02 - Python Salary Predictor Project/006 Graph plots adjusted.mp4 72.8 MB
~Get Your Files Here !/02 - Python Salary Predictor Project/007 Interactive slide connected to plots.mp4 66.3 MB
~Get Your Files Here !/03 - Machine learning Classifier project/002 Title and Side bar.mp4 64.3 MB
~Get Your Files Here !/03 - Machine learning Classifier project/003 Shape of Datasets and Number of Classes.mp4 59.3 MB
~Get Your Files Here !/02 - Python Salary Predictor Project/002 Installation of Python libraries.mp4 58.3 MB
~Get Your Files Here !/03 - Machine learning Classifier project/007 Plotting the Dataset.mp4 56.2 MB
~Get Your Files Here !/03 - Machine learning Classifier project/006 Classifiers Accuracy Score.mp4 53.5 MB
~Get Your Files Here !/02 - Python Salary Predictor Project/005 Interactive and Non-Interactive plots.mp4 47.2 MB
~Get Your Files Here !/02 - Python Salary Predictor Project/004 Image and Load Data.mp4 46.9 MB
~Get Your Files Here !/02 - Python Salary Predictor Project/003 Title and Navigation.mp4 46.0 MB
~Get Your Files Here !/02 - Python Salary Predictor Project/011 Further tips on Python Streamlit.mp4 30.1 MB
~Get Your Files Here !/02 - Python Salary Predictor Project/001 Start-up Project.mp4 24.9 MB
~Get Your Files Here !/01 - Introduction/001 Introduction.mp4 20.7 MB
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【影视】 [FreeCourseLab.com] Udemy - 2021 Python for Machine Learning & Data Science Masterclass

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23 Hierarchical Clustering/004 Hierarchical Clustering - Coding Part Two - Scikit-Learn.mp4 218.8 MB
05 Pandas/028 Pandas Project Exercise Solutions.mp4 181.0 MB
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
11 Feature Engineering and Data Preparation/003 Dealing with Outliers.mp4 126.5 MB
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
07 Seaborn Data Visualizations/002 Scatterplots with Seaborn.mp4 116.5 MB
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
07 Seaborn Data Visualizations/014 Seaborn Plot Exercises Solutions.mp4 110.8 MB
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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【影视】 [GigaCourse.Com] Udemy - Machine Learning Interview Questions & Answers

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09 ML Interview Questions - part 9/001 ML Interview Questions - part 9.mp4 57.0 MB
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【影视】 Udemy - The Memory Improvement And Learning MasterClass For Success (AKUMA)

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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
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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
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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
~Get Your Files Here !/[6] 5. Stick with Your Learning Plan/[3] Celebrate your progress.srt 7.6 kB

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

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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】 Machine Learning & Data Science A-Z Hands-on Python 2021

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06 Supervised Learning - Regression/008 Random Forest Model Development.mp4 258.2 MB
05 Supervised Learning - Classification/001 Supervised Learning Models - Introduction and Understanding the Data.mp4 245.1 MB
05 Supervised Learning - Classification/004 k-NN Training-Set and Test-Set Creation.mp4 239.5 MB
03 Data Preprocessing/006 Missing Values2.mp4 230.0 MB
06 Supervised Learning - Regression/006 Polynomial Linear Regression Model Development.mp4 229.8 MB
06 Supervised Learning - Regression/001 Simple and Multiple Linear Regression Concepts.mp4 222.5 MB
03 Data Preprocessing/003 Statistics2.mp4 217.6 MB
02 Machine Learning Useful Packages (Libraries)/013 Visualization with Matplotlib2.mp4 215.2 MB
02 Machine Learning Useful Packages (Libraries)/011 Pandas4.mp4 212.9 MB
02 Machine Learning Useful Packages (Libraries)/014 Visualization with Matplotlib3.mp4 198.0 MB
03 Data Preprocessing/012 Normalization.mp4 195.9 MB
05 Supervised Learning - Classification/013 Model Evaluation - Calculating with Python.mp4 182.5 MB
06 Supervised Learning - Regression/004 Evaluation Metrics - Implementation.mp4 167.7 MB
03 Data Preprocessing/001 Reading and Modifying a Dataset.mp4 162.1 MB
02 Machine Learning Useful Packages (Libraries)/006 NumPy5.mp4 160.1 MB
07 Unsupervised Learning - Clustering Techniques/010 Hierarchical Clustering Model Development.mp4 153.0 MB
02 Machine Learning Useful Packages (Libraries)/015 Visualization with Matplotlib4.mp4 149.9 MB
05 Supervised Learning - Classification/003 k-NN Model Development.mp4 147.5 MB
02 Machine Learning Useful Packages (Libraries)/007 NumPy6.mp4 141.0 MB
08 Hyper Parameter Optimization (Model Tuning)/004 k-NN - Model Tuning.mp4 140.1 MB

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