learning python -移花宫 -武林禁地，闲人禁止入内

Combo.4.Modulos.Machine.Learning.Com.Python

7. Módulo 1 - Confusion matrix e normalização/2. Medição de desempenho ROCAUC (Conceito + Matemática o que o algoritmo faz debaixo dos panos)/1. aula.mp4 1.4 GB
22. Módulo 2 - Support Vector Machine (SVM)/1. SVM (Conceito + Matemática o que o algoritmo faz debaixo dos panos) – parte 1/1. SVMteoria1.mp4 1.3 GB
10. Módulo 1 - Decision Trees/1. Decision Trees (Conceito + Matemática o que o algoritmo faz debaixo dos panos) – Parte 1 entropia/1. aula.mp4 1.2 GB
23. Módulo 2 - Sistemas de Recomendação/5. Método Matrix Factorization SVD++ (Teoria)/1. Matrix Factorization.mp4 1.2 GB
16. Módulo 2 - PCA/1. Principal Component Analysis - PCA (Conceito + Matemática o que o algoritmo faz debaixo dos panos)/1. aula.mp4 1.2 GB
19. Módulo 2 - AdaBoost/1. AdaBoost (Conceito + Matemática o que o algoritmo faz debaixo dos panos)/1. ADAboostTeoria.mp4 1.1 GB
30. Módulo 3 - Visão Computacional/46. Style Transfer (teoria)/1. Style Transfer Teoria.mp4 1.0 GB
15. Módulo 2 - Aprendizado não supervisionado/2. Clustering K Means (Conceito + Matemática o que o algoritmo faz debaixo dos panos)/1. aula.mp4 1.0 GB
20. Módulo 2 - GradientBoosting/1. GradientBoosting (Conceito + Matemática o que o algoritmo faz debaixo dos panos) – parte 1/1. GB teoria 1.mp4 857.4 MB
5. Módulo 1 - Validação cruzada e ajuste fino dos parâmetros/1. Validação cruzada Kfold (Teoria o que o algoritmo faz debaixo dos panos)/1. Kfold Teoria.mp4 818.2 MB
4. Módulo 1 - Outros modelos de regressão linear/1. Ridge regression (Conceito + Matemática o que o algoritmo faz debaixo dos panos)/1. Ridge regression.mp4 813.3 MB
36. Módulo 4 - Aprendizado por Reforço/131. Como o Alpha-Zero funciona/1. Alphazero.mp4 812.7 MB
22. Módulo 2 - Support Vector Machine (SVM)/2. SVM (Conceito + Matemática o que o algoritmo faz debaixo dos panos) – parte 2/1. SVMteoria2.mp4 743.7 MB
10. Módulo 1 - Decision Trees/4. Decision Trees (Conceito + Matemática o que o algoritmo faz debaixo dos panos) – Parte 3 regressão/1. aula.mp4 734.4 MB
11. Módulo 1 - Feature Selection/3. Feature selection qui-quadrado (Conceito + Matemática o que o algoritmo faz debaixo dos panos)/1. aula.mp4 732.4 MB
11. Módulo 1 - Feature Selection/5. Feature selection f_classif (Conceito + Matemática o que o algoritmo faz debaixo dos panos)/1. aula.mp4 707.8 MB
20. Módulo 2 - GradientBoosting/2. GradientBoosting (Conceito + Matemática o que o algoritmo faz debaixo dos panos) – parte 2/1. GB teoria 2.mp4 707.8 MB
10. Módulo 1 - Decision Trees/2. Decision Trees (Conceito + Matemática o que o algoritmo faz debaixo dos panos) – Parte 2 índice GINI/1. aula.mp4 689.0 MB
25. Módulo 2 - Testando seus Conhecimentos/1. Buscando a melhor performance possível/1. MelhorPerformance.mp4 655.8 MB
34. Módulo 4 - Séries Temporais e Redes Neurais Recorrentes/4. Truncated Backpropagation Through Time (TBTT)/1. RNN4.mp4 606.0 MB

[磁力链接] 添加时间:2023-12-18 大小:66.1 GB 最近下载:2025-05-01 热度:213

[FreeCourseSite.com] Udemy - Machine Learning and Data Science Hands-on with Python and R

2. Machine Learning with Tensorflow for Beginners/41. Title of the Plot.vtt 180.9 MB
2. Machine Learning with Tensorflow for Beginners/107. Tensorflow-Playground.mp4 143.3 MB
2. Machine Learning with Tensorflow for Beginners/14. Getting started with Anaconda.mp4 142.8 MB
10. Natural Language Processing (NLP) Tutorials/6. Replacing Contractions.mp4 141.6 MB
12. Machine Learning with R/108. Average of Quarter Denationalization.mp4 133.1 MB
12. Machine Learning with R/55. Creating a Graph for Kmeans Clustering.mp4 132.8 MB
3. Machine Learning Project #1 - Shipping and Time Estimation/8. Assigning a Training Set.mp4 131.3 MB
12. Machine Learning with R/54. Example of Kmeans Dataset.mp4 128.6 MB
12. Machine Learning with R/126. More on Rstudio in Market Analysis.mp4 128.5 MB
12. Machine Learning with R/85. R Type Model.mp4 127.2 MB
4. Machine Learning Project #2 - Supply Chain-Demand Trends Analysis/3. Checking the Function Argument.mp4 127.1 MB
2. Machine Learning with Tensorflow for Beginners/79. Numeric Hosing Data.mp4 126.1 MB
3. Machine Learning Project #1 - Shipping and Time Estimation/13. Normalization and Discretization.mp4 125.3 MB
12. Machine Learning with R/117. Example of Dataset Boosting in Gradient Continues.mp4 118.7 MB
2. Machine Learning with Tensorflow for Beginners/58. Grid.mp4 116.2 MB
2. Machine Learning with Tensorflow for Beginners/19. Arrays.mp4 115.7 MB
13. BIP - Business Intelligence Publisher using Siebel/8. Showing Report Views on Application.mp4 115.4 MB
2. Machine Learning with Tensorflow for Beginners/52. Pairplot.mp4 115.1 MB
2. Machine Learning with Tensorflow for Beginners/23. Universal Functions.mp4 114.9 MB
12. Machine Learning with R/101. Forecasting Using Stock Price.mp4 114.2 MB

[磁力链接] 添加时间:2021-04-13 大小:33.1 GB 最近下载:2025-10-19 热度:1935

Machine Learning and Data Science Hands-on with Python and R

Machine Learning and Data Science Hands-on with Python and R/2. Machine Learning with Tensorflow for Beginners/107. Tensorflow-Playground.mp4 143.3 MB
Machine Learning and Data Science Hands-on with Python and R/2. Machine Learning with Tensorflow for Beginners/14. Getting started with Anaconda.mp4 142.8 MB
Machine Learning and Data Science Hands-on with Python and R/10. Natural Language Processing (NLP) Tutorials/6. Replacing Contractions.mp4 141.6 MB
Machine Learning and Data Science Hands-on with Python and R/12. Machine Learning with R/108. Average of Quarter Denationalization.mp4 133.1 MB
Machine Learning and Data Science Hands-on with Python and R/12. Machine Learning with R/55. Creating a Graph for Kmeans Clustering.mp4 132.8 MB
Machine Learning and Data Science Hands-on with Python and R/3. Machine Learning Project #1 - Shipping and Time Estimation/8. Assigning a Training Set.mp4 131.3 MB
Machine Learning and Data Science Hands-on with Python and R/12. Machine Learning with R/54. Example of Kmeans Dataset.mp4 128.6 MB
Machine Learning and Data Science Hands-on with Python and R/12. Machine Learning with R/126. More on Rstudio in Market Analysis.mp4 128.5 MB
Machine Learning and Data Science Hands-on with Python and R/12. Machine Learning with R/85. R Type Model.mp4 127.2 MB
Machine Learning and Data Science Hands-on with Python and R/4. Machine Learning Project #2 - Supply Chain-Demand Trends Analysis/3. Checking the Function Argument.mp4 127.1 MB
Machine Learning and Data Science Hands-on with Python and R/2. Machine Learning with Tensorflow for Beginners/79. Numeric Hosing Data.mp4 126.1 MB
Machine Learning and Data Science Hands-on with Python and R/3. Machine Learning Project #1 - Shipping and Time Estimation/13. Normalization and Discretization.mp4 125.3 MB
Machine Learning and Data Science Hands-on with Python and R/12. Machine Learning with R/117. Example of Dataset Boosting in Gradient Continues.mp4 118.7 MB
Machine Learning and Data Science Hands-on with Python and R/2. Machine Learning with Tensorflow for Beginners/58. Grid.mp4 116.2 MB
Machine Learning and Data Science Hands-on with Python and R/2. Machine Learning with Tensorflow for Beginners/19. Arrays.mp4 115.7 MB
Machine Learning and Data Science Hands-on with Python and R/13. BIP - Business Intelligence Publisher using Siebel/8. Showing Report Views on Application.mp4 115.4 MB
Machine Learning and Data Science Hands-on with Python and R/2. Machine Learning with Tensorflow for Beginners/52. Pairplot.mp4 115.1 MB
Machine Learning and Data Science Hands-on with Python and R/2. Machine Learning with Tensorflow for Beginners/23. Universal Functions.mp4 114.9 MB
Machine Learning and Data Science Hands-on with Python and R/12. Machine Learning with R/101. Forecasting Using Stock Price.mp4 114.2 MB
Machine Learning and Data Science Hands-on with Python and R/7. Machine Learning Project #5 - Fraud Detection in Credit Payments/10. VRS.mp4 112.7 MB

[磁力链接] 添加时间:2024-01-07 大小:32.4 GB 最近下载:2025-09-30 热度:2238

Udemy - Python and Machine Learning for Complete Beginners (3.2023)

21 - Principal Component Analysis/438 - A Solution to the PCA Exercise.mp4 166.5 MB
2 - Loops and Conditions/38 - A Solution to the Boolean Operators Exercise.mp4 150.8 MB
18 - Clustering Analysing Clustered Data/388 - Iris Exercise Solution.mp4 145.2 MB
14 - Numpy Numerical Python/287 - Creating Numpy Arrays.mp4 135.8 MB
19 - Naive Bayes Making Predictions on the Basis of Probabilities/408 - Bayes Theorem.mp4 134.9 MB
9 - Conways Game of Life/193 - Getting Widget Sizes.mp4 126.7 MB
21 - Principal Component Analysis/442 - Character Recognition.mp4 125.0 MB
8 - ObjectOriented Programming/186 - The Property Class.mp4 123.9 MB
22 - Artificial Neural Networks ANNs/453 - An ANN for Recognising Digits.mp4 122.2 MB
22 - Artificial Neural Networks ANNs/449 - A Basic ANN.mp4 122.1 MB
15 - Graphs and Plotting/318 - Scatter Plots.mp4 120.6 MB
15 - Graphs and Plotting/313 - Word Length Plot Solution First Part.mp4 120.5 MB
21 - Principal Component Analysis/432 - Explained Variance Ratios.mp4 119.0 MB
13 - Reading and Writing Files/280 - Game of Life Save and Load.mp4 118.2 MB
13 - Reading and Writing Files/273 - Numbers Versus Bytes.mp4 118.0 MB
18 - Clustering Analysing Clustered Data/407 - Using KNeighborsClassifier.mp4 117.8 MB
21 - Principal Component Analysis/443 - Configuring Logistic Regression.mp4 117.6 MB
19 - Naive Bayes Making Predictions on the Basis of Probabilities/416 - Naive Bayes Classifiers.mp4 115.1 MB
9 - Conways Game of Life/201 - Implementing the Game of Life Rules.mp4 114.6 MB
18 - Clustering Analysing Clustered Data/401 - Determining Epsilon.mp4 114.1 MB

[磁力链接] 添加时间:2025-09-12 大小:30.7 GB 最近下载:2025-10-25 热度:187

Curso completo de Machine Learning Data Science en Python - COMPLETO

8. Regresión logística con Python/7. Estimación con el método de máxima verosimilitud.mp4 476.4 MB
8. Regresión logística con Python/8. Crear un modelo logístico desde cero.mp4 461.6 MB
9. Clustering y clasificación/2. ¿Qué es y para qué sirve el clustering.mp4 347.6 MB
7. Regresión lineal con Python/19. Transformar las variables en relaciones no lineales.mp4 333.6 MB
14. Análisis de componentes principales/3. Demostración de cómo se hace un ACP.mp4 325.2 MB
10. Árboles y bosques aleatorios/5. Algoritmos para la generación de árboles de clasificación.mp4 323.2 MB
11. Máquinas de Soporte Vectorial/14. Práctica de SVM reconocimiento facial a lo CSI.mp4 322.4 MB
9. Clustering y clasificación/3. El concepto de distancia.mp4 320.8 MB
8. Regresión logística con Python/9. Análisis exploratorio de los datos.mp4 315.2 MB
9. Clustering y clasificación/17. Implementando la técnica del codo y el coeficiente de la silueta.mp4 313.1 MB
10. Árboles y bosques aleatorios/4. Entropía y ganancia de Información.mp4 310.3 MB
7. Regresión lineal con Python/16. Variables categóricas en una regresión lineal.mp4 298.3 MB
8. Regresión logística con Python/16. Implementación de las curvas ROC en Python.mp4 296.5 MB
15. Introducción a las redes neuronales y al deep learning con TensorFlow/7. La carga del dataset de imágenes.mp4 295.8 MB
7. Regresión lineal con Python/5. Sumas de los cuadrados totales, de las diferencias y de la regresión.mp4 294.4 MB
11. Máquinas de Soporte Vectorial/3. El problema de clasificación no óptimo.mp4 286.7 MB
11. Máquinas de Soporte Vectorial/15. Práctica de SVM Clasificación de las flores de Iris.mp4 281.7 MB
14. Análisis de componentes principales/6. Plotly, la librería de gráficos personalizados e interactivos.mp4 280.2 MB
9. Clustering y clasificación/10. Un clustering completo por donde cortamos el dendrograma.mp4 275.9 MB
9. Clustering y clasificación/6. Uniendo datos manualmente.mp4 265.8 MB

[磁力链接] 添加时间:2021-03-21 大小:28.0 GB 最近下载:2025-10-25 热度:1333

[FreeCourseSite.com] Udemy - A deep understanding of deep learning (with Python intro)

19 - Understand and design CNNs/177 - Examine feature map activations.mp4 432.2 MB
22 - Style transfer/205 - Transferring the screaming bathtub.mp4 361.5 MB
19 - Understand and design CNNs/176 - Classify Gaussian blurs.mp4 293.3 MB
24 - RNNs Recurrent Neural Networks and GRULSTM/218 - CodeChallenge sine wave extrapolation.mp4 272.5 MB
18 - Convolution and transformations/163 - Convolution in code.mp4 270.8 MB
24 - RNNs Recurrent Neural Networks and GRULSTM/217 - Predicting alternating sequences.mp4 259.1 MB
26 - Where to go from here/229 - How to read academic DL papers.mp4 232.8 MB
19 - Understand and design CNNs/184 - The EMNIST dataset letter recognition.mp4 230.7 MB
19 - Understand and design CNNs/174 - CNN to classify MNIST digits.mp4 228.4 MB
24 - RNNs Recurrent Neural Networks and GRULSTM/222 - Lorem ipsum.mp4 226.2 MB
7 - ANNs Artificial Neural Networks/52 - Multioutput ANN iris dataset.mp4 225.5 MB
23 - Generative adversarial networks/210 - CNN GAN with Gaussians.mp4 224.6 MB
21 - Transfer learning/200 - Pretraining with autoencoders.mp4 218.8 MB
19 - Understand and design CNNs/180 - Do autoencoders clean Gaussians.mp4 216.1 MB
9 - Regularization/72 - Dropout regularization in practice.mp4 211.2 MB
21 - Transfer learning/198 - Transfer learning with ResNet18.mp4 210.9 MB
16 - Autoencoders/157 - Autoencoder with tied weights.mp4 210.4 MB
7 - ANNs Artificial Neural Networks/47 - ANN for classifying qwerties.mp4 205.8 MB
10 - Metaparameters activations optimizers/82 - The wine quality dataset.mp4 203.8 MB
18 - Convolution and transformations/171 - Image transforms.mp4 202.3 MB

[磁力链接] 添加时间:2023-12-18 大小:25.4 GB 最近下载:2025-10-26 热度:5812

Udemy - A deep understanding of deep learning (with Python intro)

19 - Understand and design CNNs/177 - Examine feature map activations.mp4 432.2 MB
22 - Style transfer/205 - Transferring the screaming bathtub.mp4 361.5 MB
19 - Understand and design CNNs/176 - Classify Gaussian blurs.mp4 293.3 MB
24 - RNNs Recurrent Neural Networks and GRULSTM/218 - CodeChallenge sine wave extrapolation.mp4 272.5 MB
18 - Convolution and transformations/163 - Convolution in code.mp4 270.8 MB
24 - RNNs Recurrent Neural Networks and GRULSTM/217 - Predicting alternating sequences.mp4 259.1 MB
26 - Where to go from here/229 - How to read academic DL papers.mp4 232.8 MB
19 - Understand and design CNNs/184 - The EMNIST dataset letter recognition.mp4 230.7 MB
19 - Understand and design CNNs/174 - CNN to classify MNIST digits.mp4 228.4 MB
24 - RNNs Recurrent Neural Networks and GRULSTM/222 - Lorem ipsum.mp4 226.2 MB
7 - ANNs Artificial Neural Networks/52 - Multioutput ANN iris dataset.mp4 225.5 MB
23 - Generative adversarial networks/210 - CNN GAN with Gaussians.mp4 224.6 MB
21 - Transfer learning/200 - Pretraining with autoencoders.mp4 218.8 MB
19 - Understand and design CNNs/180 - Do autoencoders clean Gaussians.mp4 216.1 MB
9 - Regularization/72 - Dropout regularization in practice.mp4 211.2 MB
21 - Transfer learning/198 - Transfer learning with ResNet18.mp4 210.9 MB
16 - Autoencoders/157 - Autoencoder with tied weights.mp4 210.4 MB
7 - ANNs Artificial Neural Networks/47 - ANN for classifying qwerties.mp4 205.8 MB
10 - Metaparameters activations optimizers/82 - The wine quality dataset.mp4 203.8 MB
18 - Convolution and transformations/171 - Image transforms.mp4 202.3 MB

[磁力链接] 添加时间:2023-12-18 大小:25.4 GB 最近下载:2025-10-25 热度:481

Udemy - A deep understanding of deep learning (with Python intro) 2-2023

19 - Understand and design CNNs/177 - Examine feature map activations.mp4 432.2 MB
22 - Style transfer/205 - Transferring the screaming bathtub.mp4 361.5 MB
19 - Understand and design CNNs/176 - Classify Gaussian blurs.mp4 293.3 MB
24 - RNNs Recurrent Neural Networks and GRULSTM/218 - CodeChallenge sine wave extrapolation.mp4 272.5 MB
18 - Convolution and transformations/163 - Convolution in code.mp4 270.8 MB
24 - RNNs Recurrent Neural Networks and GRULSTM/217 - Predicting alternating sequences.mp4 259.1 MB
26 - Where to go from here/229 - How to read academic DL papers.mp4 232.8 MB
19 - Understand and design CNNs/184 - The EMNIST dataset letter recognition.mp4 230.7 MB
19 - Understand and design CNNs/174 - CNN to classify MNIST digits.mp4 228.4 MB
24 - RNNs Recurrent Neural Networks and GRULSTM/222 - Lorem ipsum.mp4 226.2 MB
7 - ANNs Artificial Neural Networks/52 - Multioutput ANN iris dataset.mp4 225.5 MB
23 - Generative adversarial networks/210 - CNN GAN with Gaussians.mp4 224.6 MB
21 - Transfer learning/200 - Pretraining with autoencoders.mp4 218.8 MB
19 - Understand and design CNNs/180 - Do autoencoders clean Gaussians.mp4 216.1 MB
9 - Regularization/72 - Dropout regularization in practice.mp4 211.2 MB
21 - Transfer learning/198 - Transfer learning with ResNet18.mp4 210.9 MB
16 - Autoencoders/157 - Autoencoder with tied weights.mp4 210.4 MB
7 - ANNs Artificial Neural Networks/47 - ANN for classifying qwerties.mp4 205.8 MB
10 - Metaparameters activations optimizers/82 - The wine quality dataset.mp4 203.8 MB
18 - Convolution and transformations/171 - Image transforms.mp4 202.3 MB

[磁力链接] 添加时间:2024-05-07 大小:25.4 GB 最近下载:2025-10-23 热度:588

[08-2020] python-data-science-machine-learning-bootcamp

04 Introduction to Optimisation and the Gradient Descent Algorithm/036 [Python] - Loops and the Gradient Descent Algorithm.mp4 471.0 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/037 [Python] - Advanced Functions and the Pitfalls of Optimisation (Part 1).mp4 468.5 MB
12 Serving a Tensorflow Model through a Website/198 Introduction to OpenCV.mp4 453.3 MB
12 Serving a Tensorflow Model through a Website/200 Calculating the Centre of Mass and Shifting the Image.mp4 425.6 MB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/169 Model Evaluation and the Confusion Matrix.mp4 384.2 MB
03 Python Programming for Data Science and Machine Learning/021 [Python] - Module Imports.mp4 366.5 MB
11 Use Tensorflow to Classify Handwritten Digits/183 Different Model Architectures_ Experimenting with Dropout.mp4 352.1 MB
05 Predict House Prices with Multivariable Linear Regression/068 Working with Seaborn Pairplots & Jupyter Microbenchmarking Techniques.mp4 350.7 MB
12 Serving a Tensorflow Model through a Website/193 Loading a Tensorflow.js Model and Starting your own Server.mp4 336.9 MB
12 Serving a Tensorflow Model through a Website/195 Styling an HTML Canvas.mp4 327.6 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/038 [Python] - Tuples and the Pitfalls of Optimisation (Part 2).mp4 317.0 MB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/167 Use the Model to Make Predictions.mp4 314.6 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/040 How to Create 3-Dimensional Charts.mp4 308.6 MB
12 Serving a Tensorflow Model through a Website/196 Drawing on an HTML Canvas.mp4 305.1 MB
10 Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/166 Use Regularisation to Prevent Overfitting_ Early Stopping & Dropout Techniques.mp4 301.0 MB
12 Serving a Tensorflow Model through a Website/199 Resizing and Adding Padding to Images.mp4 300.2 MB
12 Serving a Tensorflow Model through a Website/202 Adding the Game Logic.mp4 299.9 MB
04 Introduction to Optimisation and the Gradient Descent Algorithm/039 Understanding the Learning Rate.mp4 294.2 MB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/141 Visualising the Decision Boundary.mp4 290.8 MB
08 Test and Evaluate a Naive Bayes Classifier_ Part 3/146 A Naive Bayes Implementation using SciKit Learn.mp4 283.7 MB

[磁力链接] 添加时间:2021-03-19 大小:25.0 GB 最近下载:2025-10-22 热度:10020

Udemy Машинное обучение в Python Machine Learning Data Science

Раздел 7. Seaborn/61. Scatterplots - Графики рассеяния (диаграммы рассеяния) .mp4 338.3 MB
Раздел 5. Pandas/48. Решения для проверочных упражнений по Pandas .mp4 337.2 MB
Раздел 23. Иерархическая кластеризация данных/211. Иерархическая кластеризация - Пишем код, часть 2 - Scikit-Learn.mp4 336.7 MB
Раздел 1. Вводная часть курса/4. Установка Anaconda, Python, Jupyter Notebook .mp4 333.2 MB
Раздел 13. Логистическая регрессия/137. Решения для проверочного проекта по логистической регрессии.mp4 324.8 MB
Раздел 5. Pandas/43. Input_Output в Pandas - HTML-таблицы .mp4 311.5 MB
Раздел 16. Деревья решений (Decision Trees)/161. Код в Python для деревьев решений - Часть 2 - Модель.mp4 293.3 MB
Раздел 11. Конструирование признаков (Feature Engineering)/112. Работа с отсутствующими данными (missing data) - Часть 2 - Работа по строкам.mp4 261.3 MB
Раздел 8. Большой Проект по Визуализации Данных/77. Разбор решений проекта - Часть 3.mp4 259.7 MB
Раздел 13. Логистическая регрессия/135. Мульти-классовая классификация - Логистическая регрессия - Модель.mp4 249.0 MB
Раздел 6. Matplotlib/59. Решения для проверочных упражнений по Matplotlib .mp4 242.6 MB
Раздел 10. Линейная регрессия/93. Внедрение модели и интерпретация коэффициентов.mp4 237.3 MB
Раздел 7. Seaborn/73. Решения для проверочных упражнений по Seaborn .mp4 232.7 MB
Раздел 19. Проверочный проект по моделям обучения с учителем (Supervised Learning)/181. Разбор решений - Часть 1 - Исследование данных (Exploratory Data Analysis).mp4 232.6 MB
Раздел 8. Большой Проект по Визуализации Данных/76. Разбор решений проекта - Часть 2.mp4 230.0 MB
Раздел 17. Случайные леса (Random Forests)/168. Классификация данных с помощью RandomForestClassifier - Часть 2.mp4 228.3 MB
Раздел 8. Большой Проект по Визуализации Данных/74. Обзор Проекта по Визуализации Данных.mp4 228.1 MB
Раздел 11. Конструирование признаков (Feature Engineering)/110. Работа с выбросами (outliers).mp4 226.9 MB
Раздел 19. Проверочный проект по моделям обучения с учителем (Supervised Learning)/182. Разбор решений - Часть 2 - Анализ оттока (churn analysis).mp4 224.6 MB
Раздел 7. Seaborn/67. Categorical Plots - Распределения по категориям - Код в Python .mp4 219.5 MB

[磁力链接] 添加时间:2024-02-29 大小:24.8 GB 最近下载:2025-10-23 热度:502

Udemy.Machine.Learning.de.A.a.la.Z.R.y.Python.para.Data Science

Udemy.Machine.Learning.de.A.a.la.Z.R.y.Python.para.Data Science.part02.rar 2.1 GB
Udemy.Machine.Learning.de.A.a.la.Z.R.y.Python.para.Data Science.part05.rar 2.1 GB
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Udemy.Machine.Learning.de.A.a.la.Z.R.y.Python.para.Data Science.part11.rar 2.1 GB
Udemy.Machine.Learning.de.A.a.la.Z.R.y.Python.para.Data Science.part09.rar 2.1 GB
Udemy.Machine.Learning.de.A.a.la.Z.R.y.Python.para.Data Science.part07.rar 2.1 GB
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Udemy.Machine.Learning.de.A.a.la.Z.R.y.Python.para.Data Science.part06.rar 2.1 GB
Udemy.Machine.Learning.de.A.a.la.Z.R.y.Python.para.Data Science.part01.rar 2.1 GB
Udemy.Machine.Learning.de.A.a.la.Z.R.y.Python.para.Data Science.part08.rar 2.1 GB
Udemy.Machine.Learning.de.A.a.la.Z.R.y.Python.para.Data Science.part12.rar 985.1 MB

[磁力链接] 添加时间:2021-03-13 大小:24.6 GB 最近下载:2025-10-24 热度:1893

[GigaCourse.Com] Udemy - A deep understanding of deep learning (with Python intro)

19 - Understand and design CNNs/005 Examine feature map activations.mp4 273.2 MB
22 - Style transfer/004 Transferring the screaming bathtub.mp4 227.4 MB
19 - Understand and design CNNs/012 The EMNIST dataset (letter recognition).mp4 211.1 MB
19 - Understand and design CNNs/002 CNN to classify MNIST digits.mp4 210.1 MB
24 - RNNs (Recurrent Neural Networks) (and GRULSTM)/005 CodeChallenge sine wave extrapolation.mp4 205.2 MB
24 - RNNs (Recurrent Neural Networks) (and GRULSTM)/009 Lorem ipsum.mp4 201.9 MB
07 - ANNs (Artificial Neural Networks)/013 Multi-output ANN (iris dataset).mp4 195.8 MB
19 - Understand and design CNNs/004 Classify Gaussian blurs.mp4 194.1 MB
09 - Regularization/004 Dropout regularization in practice.mp4 192.1 MB
16 - Autoencoders/006 Autoencoder with tied weights.mp4 186.4 MB
18 - Convolution and transformations/003 Convolution in code.mp4 181.5 MB
08 - Overfitting and cross-validation/006 Cross-validation -- DataLoader.mp4 180.7 MB
23 - Generative adversarial networks/002 Linear GAN with MNIST.mp4 178.2 MB
07 - ANNs (Artificial Neural Networks)/009 Learning rates comparison.mp4 176.8 MB
12 - More on data/003 CodeChallenge unbalanced data.mp4 174.3 MB
11 - FFNs (Feed-Forward Networks)/003 FFN to classify digits.mp4 169.7 MB
16 - Autoencoders/005 The latent code of MNIST.mp4 169.7 MB
24 - RNNs (Recurrent Neural Networks) (and GRULSTM)/004 Predicting alternating sequences.mp4 167.9 MB
07 - ANNs (Artificial Neural Networks)/018 Model depth vs. breadth.mp4 166.6 MB
12 - More on data/007 Data feature augmentation.mp4 166.0 MB

[磁力链接] 添加时间:2022-02-03 大小:23.6 GB 最近下载:2025-10-23 热度:4348

[FreeCourseSite.com] Udemy - A deep understanding of deep learning (with Python intro)

19 - Understand and design CNNs/005 Examine feature map activations.mp4 273.2 MB
22 - Style transfer/004 Transferring the screaming bathtub.mp4 227.4 MB
19 - Understand and design CNNs/012 The EMNIST dataset (letter recognition).mp4 211.1 MB
19 - Understand and design CNNs/002 CNN to classify MNIST digits.mp4 210.1 MB
24 - RNNs (Recurrent Neural Networks) (and GRULSTM)/005 CodeChallenge sine wave extrapolation.mp4 205.2 MB
24 - RNNs (Recurrent Neural Networks) (and GRULSTM)/009 Lorem ipsum.mp4 201.9 MB
07 - ANNs (Artificial Neural Networks)/013 Multi-output ANN (iris dataset).mp4 195.8 MB
19 - Understand and design CNNs/004 Classify Gaussian blurs.mp4 194.1 MB
09 - Regularization/004 Dropout regularization in practice.mp4 192.1 MB
16 - Autoencoders/006 Autoencoder with tied weights.mp4 186.4 MB
18 - Convolution and transformations/003 Convolution in code.mp4 181.5 MB
08 - Overfitting and cross-validation/006 Cross-validation -- DataLoader.mp4 180.7 MB
23 - Generative adversarial networks/002 Linear GAN with MNIST.mp4 178.2 MB
07 - ANNs (Artificial Neural Networks)/009 Learning rates comparison.mp4 176.8 MB
12 - More on data/003 CodeChallenge unbalanced data.mp4 174.3 MB
11 - FFNs (Feed-Forward Networks)/003 FFN to classify digits.mp4 169.7 MB
16 - Autoencoders/005 The latent code of MNIST.mp4 169.7 MB
24 - RNNs (Recurrent Neural Networks) (and GRULSTM)/004 Predicting alternating sequences.mp4 167.9 MB
07 - ANNs (Artificial Neural Networks)/018 Model depth vs. breadth.mp4 166.6 MB
12 - More on data/007 Data feature augmentation.mp4 166.0 MB

[磁力链接] 添加时间:2022-02-01 大小:23.6 GB 最近下载:2025-06-24 热度:480

A deep understanding of deep learning (with Python intro)

[TutsNode.com] - A deep understanding of deep learning (with Python intro)/19 Understand and design CNNs/005 Examine feature map activations.mp4 273.2 MB
[TutsNode.com] - A deep understanding of deep learning (with Python intro)/22 Style transfer/004 Transferring the screaming bathtub.mp4 227.4 MB
[TutsNode.com] - A deep understanding of deep learning (with Python intro)/19 Understand and design CNNs/012 The EMNIST dataset (letter recognition).mp4 211.1 MB
[TutsNode.com] - A deep understanding of deep learning (with Python intro)/19 Understand and design CNNs/002 CNN to classify MNIST digits.mp4 210.1 MB
[TutsNode.com] - A deep understanding of deep learning (with Python intro)/07 ANNs/013 Multi-output ANN (iris dataset).mp4 195.8 MB
[TutsNode.com] - A deep understanding of deep learning (with Python intro)/19 Understand and design CNNs/004 Classify Gaussian blurs.mp4 194.1 MB
[TutsNode.com] - A deep understanding of deep learning (with Python intro)/09 Regularization/004 Dropout regularization in practice.mp4 192.1 MB
[TutsNode.com] - A deep understanding of deep learning (with Python intro)/16 Autoencoders/006 Autoencoder with tied weights.mp4 186.4 MB
[TutsNode.com] - A deep understanding of deep learning (with Python intro)/18 Convolution and transformations/003 Convolution in code.mp4 181.5 MB
[TutsNode.com] - A deep understanding of deep learning (with Python intro)/08 Overfitting and cross-validation/006 Cross-validation -- DataLoader.mp4 180.7 MB
[TutsNode.com] - A deep understanding of deep learning (with Python intro)/23 Generative adversarial networks/002 Linear GAN with MNIST.mp4 178.2 MB
[TutsNode.com] - A deep understanding of deep learning (with Python intro)/07 ANNs/009 Learning rates comparison.mp4 176.8 MB
[TutsNode.com] - A deep understanding of deep learning (with Python intro)/12 More on data/003 CodeChallenge_ unbalanced data.mp4 174.3 MB
[TutsNode.com] - A deep understanding of deep learning (with Python intro)/11 FFNs/003 FFN to classify digits.mp4 169.7 MB
[TutsNode.com] - A deep understanding of deep learning (with Python intro)/16 Autoencoders/005 The latent code of MNIST.mp4 169.7 MB
[TutsNode.com] - A deep understanding of deep learning (with Python intro)/07 ANNs/018 Model depth vs. breadth.mp4 166.6 MB
[TutsNode.com] - A deep understanding of deep learning (with Python intro)/12 More on data/007 Data feature augmentation.mp4 166.0 MB
[TutsNode.com] - A deep understanding of deep learning (with Python intro)/21 Transfer learning/007 Pretraining with autoencoders.mp4 164.2 MB
[TutsNode.com] - A deep understanding of deep learning (with Python intro)/14 FFN milestone projects/004 Project 2_ My solution.mp4 163.3 MB
[TutsNode.com] - A deep understanding of deep learning (with Python intro)/21 Transfer learning/008 CIFAR10 with autoencoder-pretrained model.mp4 160.8 MB

[磁力链接] 添加时间:2022-03-14 大小:22.9 GB 最近下载:2025-10-22 热度:8470

[GigaCourse.Com] Udemy - A deep understanding of deep learning (with Python intro)

19 Understand and design CNNs/005 Examine feature map activations.mp4 273.2 MB
22 Style transfer/004 Transferring the screaming bathtub.mp4 227.4 MB
19 Understand and design CNNs/012 The EMNIST dataset (letter recognition).mp4 211.1 MB
19 Understand and design CNNs/002 CNN to classify MNIST digits.mp4 210.1 MB
07 ANNs/013 Multi-output ANN (iris dataset).mp4 195.8 MB
19 Understand and design CNNs/004 Classify Gaussian blurs.mp4 194.1 MB
09 Regularization/004 Dropout regularization in practice.mp4 192.1 MB
16 Autoencoders/006 Autoencoder with tied weights.mp4 186.4 MB
18 Convolution and transformations/003 Convolution in code.mp4 181.5 MB
08 Overfitting and cross-validation/006 Cross-validation -- DataLoader.mp4 180.7 MB
23 Generative adversarial networks/002 Linear GAN with MNIST.mp4 178.2 MB
07 ANNs/009 Learning rates comparison.mp4 176.8 MB
12 More on data/003 CodeChallenge_ unbalanced data.mp4 174.3 MB
11 FFNs/003 FFN to classify digits.mp4 169.7 MB
16 Autoencoders/005 The latent code of MNIST.mp4 169.7 MB
07 ANNs/018 Model depth vs. breadth.mp4 166.6 MB
12 More on data/007 Data feature augmentation.mp4 166.0 MB
21 Transfer learning/007 Pretraining with autoencoders.mp4 164.2 MB
14 FFN milestone projects/004 Project 2_ My solution.mp4 163.3 MB
21 Transfer learning/008 CIFAR10 with autoencoder-pretrained model.mp4 160.8 MB

[磁力链接] 添加时间:2022-03-18 大小:22.7 GB 最近下载:2025-10-25 热度:212

[FreeCourseSite.com] Udemy - A deep understanding of deep learning (with Python intro)

19 Understand and design CNNs/005 Examine feature map activations.mp4 273.2 MB
22 Style transfer/004 Transferring the screaming bathtub.mp4 227.4 MB
19 Understand and design CNNs/012 The EMNIST dataset (letter recognition).mp4 211.1 MB
19 Understand and design CNNs/002 CNN to classify MNIST digits.mp4 210.1 MB
07 ANNs/013 Multi-output ANN (iris dataset).mp4 195.8 MB
19 Understand and design CNNs/004 Classify Gaussian blurs.mp4 194.1 MB
09 Regularization/004 Dropout regularization in practice.mp4 192.1 MB
16 Autoencoders/006 Autoencoder with tied weights.mp4 186.4 MB
18 Convolution and transformations/003 Convolution in code.mp4 181.5 MB
08 Overfitting and cross-validation/006 Cross-validation -- DataLoader.mp4 180.7 MB
23 Generative adversarial networks/002 Linear GAN with MNIST.mp4 178.2 MB
07 ANNs/009 Learning rates comparison.mp4 176.8 MB
12 More on data/003 CodeChallenge_ unbalanced data.mp4 174.3 MB
11 FFNs/003 FFN to classify digits.mp4 169.7 MB
16 Autoencoders/005 The latent code of MNIST.mp4 169.7 MB
07 ANNs/018 Model depth vs. breadth.mp4 166.6 MB
12 More on data/007 Data feature augmentation.mp4 166.0 MB
21 Transfer learning/007 Pretraining with autoencoders.mp4 164.2 MB
14 FFN milestone projects/004 Project 2_ My solution.mp4 163.3 MB
21 Transfer learning/008 CIFAR10 with autoencoder-pretrained model.mp4 160.8 MB

[磁力链接] 添加时间:2022-01-20 大小:22.7 GB 最近下载:2025-10-15 热度:1058

[Udemy] A deep understanding of deep learning (with Python intro) (08.2021)

19 Understand and design CNNs/005 Examine feature map activations.mp4 273.2 MB
22 Style transfer/004 Transferring the screaming bathtub.mp4 227.4 MB
19 Understand and design CNNs/012 The EMNIST dataset (letter recognition).mp4 211.1 MB
19 Understand and design CNNs/002 CNN to classify MNIST digits.mp4 210.1 MB
07 ANNs/013 Multi-output ANN (iris dataset).mp4 195.8 MB
19 Understand and design CNNs/004 Classify Gaussian blurs.mp4 194.1 MB
09 Regularization/004 Dropout regularization in practice.mp4 192.1 MB
16 Autoencoders/006 Autoencoder with tied weights.mp4 186.4 MB
18 Convolution and transformations/003 Convolution in code.mp4 181.5 MB
08 Overfitting and cross-validation/006 Cross-validation -- DataLoader.mp4 180.7 MB
23 Generative adversarial networks/002 Linear GAN with MNIST.mp4 178.2 MB
07 ANNs/009 Learning rates comparison.mp4 176.8 MB
12 More on data/003 CodeChallenge_ unbalanced data.mp4 174.3 MB
11 FFNs/003 FFN to classify digits.mp4 169.7 MB
16 Autoencoders/005 The latent code of MNIST.mp4 169.7 MB
07 ANNs/018 Model depth vs. breadth.mp4 166.6 MB
12 More on data/007 Data feature augmentation.mp4 166.0 MB
21 Transfer learning/007 Pretraining with autoencoders.mp4 164.2 MB
14 FFN milestone projects/004 Project 2_ My solution.mp4 163.3 MB
21 Transfer learning/008 CIFAR10 with autoencoder-pretrained model.mp4 160.8 MB

[磁力链接] 添加时间:2022-01-13 大小:22.7 GB 最近下载:2025-10-17 热度:4052

[GigaCourse.Com] Udemy - Machine Learning in Python with 5 Machine Learning Projects

12. Tree Based Models/2. Attribute selection method- Gini Index and Entropy.mp4 229.3 MB
11. Introduction to KNN, SVM, Naive Bayes/6. Introduction to Naive Bayes.mp4 183.2 MB
13. Boosting Models/2. Intuition for Adaboost and Gradient Boosting.mp4 160.7 MB
10. Logistic Regression/8. Using ROC-AUC score to analyze the performance of model.mp4 154.8 MB
10. Logistic Regression/6. How to analyze performance of a classification model.mp4 153.3 MB
13. Boosting Models/7. Introudction to Ensembling techniques.mp4 140.5 MB
20. Predicting Health Expense of Customers/8. Applying Linear Regression Model.mp4 134.3 MB
2. Python for Data Analysis/17. Time Complexity.mp4 126.0 MB
2. Python for Data Analysis/21. Insertion and Selection Sort.mp4 125.8 MB
1. Python Fundamentals/4. Built in Data Types and Type Casting.mp4 125.7 MB
18. Time Series Forecasting/8. Handling Missing Values.mp4 122.1 MB
2. Python for Data Analysis/22. Merge Sort.mp4 121.0 MB
17. Recommendation Engines/19. Introduction to SVD.mp4 117.5 MB
2. Python for Data Analysis/19. Binary Search.mp4 114.9 MB
9. Linear Regression/6. Analyzing the performance of Regression models.mp4 114.3 MB
11. Introduction to KNN, SVM, Naive Bayes/1. Introduction to Support Vector machines.mp4 113.4 MB
9. Linear Regression/9. Applying real time prediction on our model.mp4 112.8 MB
9. Linear Regression/7. R2 score and adjuted R2 score intuition.mp4 112.2 MB
10. Logistic Regression/1. Introduction to Logistic Regression.mp4 111.6 MB
5. Data Cleaning/24. Data Cleaning on Naukri Dataset.mp4 111.4 MB

[磁力链接] 添加时间:2022-04-06 大小:22.4 GB 最近下载:2025-10-04 热度:2203

[Tutorialsplanet.NET] Udemy - Machine Learning in Python with 5 Machine Learning Projects

12. Tree Based Models/2. Attribute selection method- Gini Index and Entropy.mp4 229.3 MB
11. Introduction to KNN, SVM, Naive Bayes/6. Introduction to Naive Bayes.mp4 183.2 MB
13. Boosting Models/2. Intuition for Adaboost and Gradient Boosting.mp4 160.7 MB
10. Logistic Regression/8. Using ROC-AUC score to analyze the performance of model.mp4 154.8 MB
10. Logistic Regression/6. How to analyze performance of a classification model.mp4 153.3 MB
13. Boosting Models/7. Introudction to Ensembling techniques.mp4 140.5 MB
20. Predicting Health Expense of Customers/8. Applying Linear Regression Model.mp4 134.3 MB
2. Python for Data Analysis/17. Time Complexity.mp4 126.0 MB
2. Python for Data Analysis/21. Insertion and Selection Sort.mp4 125.8 MB
1. Python Fundamentals/4. Built in Data Types and Type Casting.mp4 125.7 MB
18. Time Series Forecasting/8. Handling Missing Values.mp4 122.1 MB
2. Python for Data Analysis/22. Merge Sort.mp4 121.0 MB
17. Recommendation Engines/19. Introduction to SVD.mp4 117.5 MB
2. Python for Data Analysis/19. Binary Search.mp4 114.9 MB
9. Linear Regression/6. Analyzing the performance of Regression models.mp4 114.3 MB
11. Introduction to KNN, SVM, Naive Bayes/1. Introduction to Support Vector machines.mp4 113.4 MB
9. Linear Regression/9. Applying real time prediction on our model.mp4 112.8 MB
9. Linear Regression/7. R2 score and adjuted R2 score intuition.mp4 112.2 MB
10. Logistic Regression/1. Introduction to Logistic Regression.mp4 111.6 MB
5. Data Cleaning/24. Data Cleaning on Naukri Dataset.mp4 111.4 MB

[磁力链接] 添加时间:2022-03-08 大小:22.4 GB 最近下载:2025-10-15 热度:60

[FreeCourseSite.com] Udemy - Machine Learning in Python with 5 Machine Learning Projects

12. Tree Based Models/2. Attribute selection method- Gini Index and Entropy.mp4 229.3 MB
11. Introduction to KNN, SVM, Naive Bayes/6. Introduction to Naive Bayes.mp4 183.2 MB
13. Boosting Models/2. Intuition for Adaboost and Gradient Boosting.mp4 160.7 MB
10. Logistic Regression/8. Using ROC-AUC score to analyze the performance of model.mp4 154.8 MB
10. Logistic Regression/6. How to analyze performance of a classification model.mp4 153.3 MB
13. Boosting Models/7. Introudction to Ensembling techniques.mp4 140.5 MB
20. Predicting Health Expense of Customers/8. Applying Linear Regression Model.mp4 134.3 MB
2. Python for Data Analysis/17. Time Complexity.mp4 126.0 MB
2. Python for Data Analysis/21. Insertion and Selection Sort.mp4 125.8 MB
1. Python Fundamentals/4. Built in Data Types and Type Casting.mp4 125.7 MB
18. Time Series Forecasting/8. Handling Missing Values.mp4 122.1 MB
2. Python for Data Analysis/22. Merge Sort.mp4 121.0 MB
17. Recommendation Engines/19. Introduction to SVD.mp4 117.5 MB
2. Python for Data Analysis/19. Binary Search.mp4 114.9 MB
9. Linear Regression/6. Analyzing the performance of Regression models.mp4 114.3 MB
11. Introduction to KNN, SVM, Naive Bayes/1. Introduction to Support Vector machines.mp4 113.4 MB
9. Linear Regression/9. Applying real time prediction on our model.mp4 112.8 MB
9. Linear Regression/7. R2 score and adjuted R2 score intuition.mp4 112.2 MB
10. Logistic Regression/1. Introduction to Logistic Regression.mp4 111.6 MB
5. Data Cleaning/24. Data Cleaning on Naukri Dataset.mp4 111.4 MB

[磁力链接] 添加时间:2022-01-20 大小:22.4 GB 最近下载:2025-10-22 热度:1127