learning python -移花宫 -武林禁地，闲人禁止入内

[GigaCourse.Com] Udemy - Machine Learning A-Z™ - AI, Python & R + ChatGPT Bonus [2023]

41 - Kernel PCA/372 - Kernel PCA in R.mp4 418.7 MB
29 - Apriori/271 - Apriori in R Step 3.mp4 282.1 MB
36 - Artificial Neural Networks/339 - ANN in R Step 1.mp4 238.7 MB
37 - Convolutional Neural Networks/345 - dataset.zip 232.0 MB
36 - Artificial Neural Networks/341 - ANN in R Step 3.mp4 212.6 MB
20 - Naive Bayes/197 - Bayes Theorem.mp4 204.7 MB
29 - Apriori/268 - Apriori in Python Step 4.mp4 201.8 MB
43 - Model Selection/375 - Grid Search in Python.mp4 196.8 MB
37 - Convolutional Neural Networks/359 - CNN in Python FINAL DEMO.mp4 195.1 MB
35 - Part 8 Deep Learning/324 - What is Deep Learning.mp4 186.8 MB
39 - Principal Component Analysis PCA/365 - PCA in R Step 1.mp4 184.3 MB
37 - Convolutional Neural Networks/355 - CNN in Python Step 2.mp4 182.9 MB
40 - Linear Discriminant Analysis LDA/370 - LDA in R.mp4 173.3 MB
32 - Upper Confidence Bound UCB/287 - Upper Confidence Bound in R Step 3.mp4 172.7 MB
29 - Apriori/270 - Apriori in R Step 2.mp4 169.8 MB
44 - XGBoost/378 - XGBoost in Python.mp4 149.5 MB
37 - Convolutional Neural Networks/358 - CNN in Python Step 5.mp4 147.0 MB
37 - Convolutional Neural Networks/349 - Step 2 Pooling.mp4 146.2 MB
34 - Part 7 Natural Language Processing/307 - Natural Language Processing in Python Step 5.mp4 143.5 MB
39 - Principal Component Analysis PCA/363 - PCA in Python Step 1.mp4 143.0 MB

[磁力链接] 添加时间:2023-12-22 大小:17.4 GB 最近下载:2025-10-24 热度:5978

[FreeCourseSite.com] Udemy - Python-Introduction to Data Science and Machine learning A-Z

1. Introduction/2. What is Data Science.mp4 275.7 MB
8. Machine Learning/2. Presentation of Different algorithms.mp4 255.0 MB
2. Basic Statstics knowledge/3. The basics of statistics part 2.mp4 202.3 MB
2. Basic Statstics knowledge/7. The basics of statistics part 6.mp4 180.5 MB
8. Machine Learning/4. Machine learning algorithms part 2.mp4 170.4 MB
8. Machine Learning/1. Introduction to machine learning.mp4 138.4 MB
2. Basic Statstics knowledge/1. The Basics of Data.mp4 130.4 MB
2. Basic Statstics knowledge/5. The basics of statistics part 4.mp4 122.9 MB
2. Basic Statstics knowledge/6. The basics of statistics part 5.mp4 120.4 MB
2. Basic Statstics knowledge/2. The basics of statistics part 1.mp4 115.4 MB
1. Introduction/1. Introduction.mp4 106.6 MB
4. Python library Pandas/1. The Basics of Pandas.mp4 93.3 MB
3. Python library NumPy/1. Introduction to Numpy.mp4 87.5 MB
6. Python library Matplotlib/1. Introduction to Matplotlib.mp4 73.8 MB
7. Python library Seaborn/1. Introduction to Seaborn.mp4 69.9 MB
2. Basic Statstics knowledge/4. The basics of statistics part 3.mp4 69.5 MB
8. Machine Learning/5. Machine learning algorithms part 3.mp4 66.6 MB
5. Python library Scipy/1. The Basics of SciPy.mp4 65.8 MB
6. Python library Matplotlib/3. Basics of matplotlib part 1.mp4 64.6 MB
7. Python library Seaborn/3. Seaborn operations part 1.mp4 56.3 MB

[磁力链接] 添加时间:2023-12-17 大小:3.4 GB 最近下载:2025-10-24 热度:5951

[ DevCourseWeb.com ] Machine Learning with PyTorch and Scikit-Learn - Develop machine learning and deep learning models with Python

~Get Your Files Here !/9781801819312_Code/git/objects/pack/pack-0f48181b8b0c051c40c7d403bfb95ecde41a358a.pack 164.0 MB
~Get Your Files Here !/9781801819312_Code/ch08/movie_data.csv 65.9 MB
~Get Your Files Here !/9781801819312.epub 63.5 MB
~Get Your Files Here !/9781801819312-MACHINELEARNINGWITHPYTORCHANDSCIKITLEARN.pdf 30.7 MB
~Get Your Files Here !/9781801819312_Code/ch18/ch18_part1.ipynb 11.8 MB
~Get Your Files Here !/9781801819312_Code/ch17/ch17_part1.ipynb 7.4 MB
~Get Your Files Here !/9781801819312_Code/ch16/ch16-part2-gpt2.ipynb 7.0 MB
~Get Your Files Here !/9781801819312_Code/ch16/ch16-part1-self-attention.ipynb 6.1 MB
~Get Your Files Here !/9781801819312_Code/ch01/ch01.ipynb 6.0 MB
~Get Your Files Here !/9781801819312_Code/ch19/ch19.ipynb 5.0 MB
~Get Your Files Here !/9781801819312_Code/ch11/ch11.ipynb 5.0 MB
~Get Your Files Here !/9781801819312_Code/ch03/ch03.ipynb 3.7 MB
~Get Your Files Here !/9781801819312_Code/ch07/ch07.ipynb 3.6 MB
~Get Your Files Here !/9781801819312_Code/ch06/ch06.ipynb 3.2 MB
~Get Your Files Here !/9781801819312_Code/ch02/ch02.ipynb 3.0 MB
~Get Your Files Here !/9781801819312_Code/ch14/ch14_part2.ipynb 2.7 MB
~Get Your Files Here !/9781801819312_Code/ch17/ch17_part2.ipynb 2.6 MB
~Get Your Files Here !/9781801819312_Code/ch18/ch18_part2.ipynb 2.6 MB
~Get Your Files Here !/9781801819312_Code/ch17/figures/17_02.png 2.3 MB
~Get Your Files Here !/9781801819312_Code/ch04/ch04.ipynb 2.1 MB

[磁力链接] 添加时间:2022-03-16 大小:484.0 MB 最近下载:2025-10-24 热度:5915

[ DevCourseWeb.com ] Udemy - Fundamentals of Python, Machine Learning for Consultants

~Get Your Files Here !/1. Introduction to Python for Data Science/2. Python Basics - variables, data types, operations and functions.mp4 231.1 MB
~Get Your Files Here !/4. Machine Learning Data Analytics by Example/1. Inventory Forecasting - Probability Analysis.mp4 196.8 MB
~Get Your Files Here !/3. Sentiment Data Analysis and Visualization Technique/3. Visualization Technique with Seaborn.mp4 171.6 MB
~Get Your Files Here !/4. Machine Learning Data Analytics by Example/2. Linear Regression Data Analysis.mp4 170.2 MB
~Get Your Files Here !/3. Sentiment Data Analysis and Visualization Technique/2. Bitcoin Sentiment Visualization Technique using Matplotlib.mp4 151.0 MB
~Get Your Files Here !/5. Machine Learning with pySpark and Apache Spark in Databricks/3. Linear Regression with pySpark and Apache Spark.mp4 147.0 MB
~Get Your Files Here !/4. Machine Learning Data Analytics by Example/3. Clustering Data Analytics.mp4 140.6 MB
~Get Your Files Here !/2. Guideline When Building Machine Learning/2. Understanding the Architectural Layers of Data Engineer.mp4 126.5 MB
~Get Your Files Here !/5. Machine Learning with pySpark and Apache Spark in Databricks/2. Load Data into Cluster.mp4 117.8 MB
~Get Your Files Here !/1. Introduction to Python for Data Science/4. Python Data Science Library Pandas.mp4 114.5 MB
~Get Your Files Here !/2. Guideline When Building Machine Learning/3. Data Preparation as an Example.mp4 95.6 MB
~Get Your Files Here !/5. Machine Learning with pySpark and Apache Spark in Databricks/4. Where to go From Here.mp4 78.6 MB
~Get Your Files Here !/1. Introduction to Python for Data Science/5. Python Data Science Library Numpy.mp4 62.9 MB
~Get Your Files Here !/2. Guideline When Building Machine Learning/1. Guideline When Building Machine Learning.mp4 60.2 MB
~Get Your Files Here !/5. Machine Learning with pySpark and Apache Spark in Databricks/1. What is Databricks and setup Cloud Account.mp4 54.5 MB
~Get Your Files Here !/1. Introduction to Python for Data Science/1. Setting up the Python Environment.mp4 41.5 MB
~Get Your Files Here !/1. Introduction to Python for Data Science/3. Python Language Reference.mp4 31.3 MB
~Get Your Files Here !/3. Sentiment Data Analysis and Visualization Technique/1. A look at Bitcoin Sentiment Data.mp4 24.9 MB
~Get Your Files Here !/3. Sentiment Data Analysis and Visualization Technique/1.1 sentiment_dataset.json 417.1 kB
~Get Your Files Here !/3. Sentiment Data Analysis and Visualization Technique/2.2 sentiment_dataset.json 417.1 kB

[磁力链接] 添加时间:2024-03-03 大小:2.0 GB 最近下载:2025-10-25 热度:5886

Complete Data Science & Machine Learning Bootcamp - Python 3

Complete Data Science & Machine Learning Bootcamp - Python 3.zip 15.8 GB
Download more courses.url 123 Bytes
Downloaded from TutsGalaxy.com.txt 73 Bytes
TutsGalaxy.com.txt 52 Bytes

[磁力链接] 添加时间:2021-03-16 大小:15.8 GB 最近下载:2025-10-22 热度:5856

[ FreeCourseWeb.com ] Linkedin - Full-Stack Deep Learning with Python

~Get Your Files Here !/Ex_Files_Full_Stack_Deep_Learning_Python/Exercise Files/final_code/datasets/emnist-letters-train.csv 171.6 MB
~Get Your Files Here !/Ex_Files_Full_Stack_Deep_Learning_Python/Exercise Files/final_code/datasets/emnist-letters-test.csv 28.6 MB
~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/02 - Configuring and training the model using MLflow runs.mp4 16.3 MB
~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/03 - Visualizing charts, metrics, and parameters on MLflow.mp4 16.0 MB
~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/05 - Hyperparameter optimization with Hyperopt and MLflow.mp4 14.6 MB
~Get Your Files Here !/05 - 4. Model Deployment and Predictions/03 - Deploying and serving the model locally.mp4 14.4 MB
~Get Your Files Here !/02 - 1. An Overview of Full-Stack Deep Learning/04 - Setting up the environment on Google Colab.mp4 13.7 MB
~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/04 - Setting up the objective function for hyperparameter tuning.mp4 13.0 MB
~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/07 - Making predictions using MLflow artifacts.mp4 11.9 MB
~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/05 - Training a model within an MLflow run.mp4 11.7 MB
~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/02 - Logging metrics, parameters, and artifacts in MLflow.mp4 11.6 MB
~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/04 - Configuring the image classification DNN model.mp4 11.0 MB
~Get Your Files Here !/02 - 1. An Overview of Full-Stack Deep Learning/05 - Running MLflow and using ngrok to access the MLflow UI.mp4 10.8 MB
~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/01 - Loading and exploring the EMNIST dataset.mp4 10.4 MB
~Get Your Files Here !/01 - Introduction/01 - Full-stack deep learning, MLOps, and MLflow.mp4 10.3 MB
~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/01 - Preparing data for image classification using CNN.mp4 10.2 MB
~Get Your Files Here !/03 - 2. Model Training and Evaluation Using MLflow/06 - Exploring parameters and metrics in MLflow.mp4 9.5 MB
~Get Your Files Here !/05 - 4. Model Deployment and Predictions/01 - Setting up MLflow on the local machine.mp4 8.6 MB
~Get Your Files Here !/04 - 3. Model Training and Hyperparameter Tuning/06 - Identifying the best model.mp4 8.2 MB
~Get Your Files Here !/02 - 1. An Overview of Full-Stack Deep Learning/01 - Introducing full-stack deep learning.mp4 8.2 MB

[磁力链接] 添加时间:2024-02-20 大小:452.1 MB 最近下载:2025-10-25 热度:5843

[FreeCoursesOnline.Me] [Packt] Machine Learning for Algorithmic Trading Bots with Python [FCO]

05.Build Advanced Trading Algorithm/0502.Implement Scalpers Trading Strategy.mp4 127.9 MB
Exercise Files/exercise_files.zip 94.4 MB
01.Building Your First Trading Bot/0105.Fetching and Understanding the Dataset.mp4 71.6 MB
03.Build a Trading Algorithm/0303.Implement Exploit Correlation Strategy.mp4 60.7 MB
02.Design a Machine Learning Model/0202.Build and Implement Random Forests Algorithm.mp4 54.3 MB
06.Model and Strategy Evaluation/0601.Introducing Value at Risk Backtest.mp4 42.4 MB
01.Building Your First Trading Bot/0101.The Course Overview.mp4 42.0 MB
06.Model and Strategy Evaluation/0605.Conclusion and Next steps..mp4 41.2 MB
04.Design Advanced Machine Learning Model/0402.Implementing GBoosting Using Python.mp4 38.7 MB
06.Model and Strategy Evaluation/0604.Implement VaR Using SVR.mp4 38.7 MB
06.Model and Strategy Evaluation/0602.Implement Value at Risk Backtest.mp4 37.1 MB
01.Building Your First Trading Bot/0107.Evaluate the Strategy’s Performance.mp4 36.9 MB
04.Design Advanced Machine Learning Model/0403.Evaluating the Model Performance.mp4 36.0 MB
02.Design a Machine Learning Model/0201.Intuition behind Random Forests Algorithm.mp4 34.7 MB
01.Building Your First Trading Bot/0102.Introduction to Financial Machine Learning and Algorithmic Trading.mp4 32.8 MB
01.Building Your First Trading Bot/0103.Setting up the Environment.mp4 30.2 MB
01.Building Your First Trading Bot/0106.Build the Conventional Buy and Hold Strategy.mp4 26.0 MB
05.Build Advanced Trading Algorithm/0503.Evaluate Scalpers Trading Strategy.mp4 25.8 MB
02.Design a Machine Learning Model/0203.Plug-in Random Forests Implementation into Your Bot.mp4 22.6 MB
01.Building Your First Trading Bot/0104.Project Skeleton Overview.mp4 22.0 MB

[磁力链接] 添加时间:2021-03-16 大小:1.0 GB 最近下载:2025-10-26 热度:5821

[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

Natural Language Processing - Deep Learning Models in Python

Chapter 6 Recurrent Neural Networks/009. Parts-of-Speech (POS) Tagging in Tensorflow.mp4 57.2 MB
Chapter 4 Feedforward Artificial Neural Networks/013. CBOW in Tensorflow (Advanced).mp4 54.1 MB
Chapter 5 Convolutional Neural Networks/006. CNN Architecture.mp4 42.5 MB
Chapter 3 The Neuron/004. Text Classification in Tensorflow.mp4 39.5 MB
Chapter 4 Feedforward Artificial Neural Networks/004. Activation Functions.mp4 38.8 MB
Chapter 6 Recurrent Neural Networks/006. GRU and LSTM (pt 1).mp4 38.8 MB
Chapter 5 Convolutional Neural Networks/005. Convolution on Color Images.mp4 35.9 MB
Chapter 5 Convolutional Neural Networks/002. What is Convolution.mp4 35.5 MB
Chapter 3 The Neuron/002. Fitting a Line.mp4 34.0 MB
Chapter 6 Recurrent Neural Networks/005. RNNs Paying Attention to Shapes.mp4 28.8 MB
Chapter 6 Recurrent Neural Networks/007. GRU and LSTM (pt 2).mp4 25.6 MB
Chapter 4 Feedforward Artificial Neural Networks/008. Text Preprocessing Code Preparation.mp4 25.3 MB
Chapter 3 The Neuron/006. How does a model learn.mp4 23.6 MB
Chapter 4 Feedforward Artificial Neural Networks/003. The Geometrical Picture.mp4 23.5 MB
Chapter 6 Recurrent Neural Networks/008. RNN for Text Classification in Tensorflow.mp4 22.1 MB
Chapter 6 Recurrent Neural Networks/004. RNN Code Preparation.mp4 21.5 MB
Chapter 4 Feedforward Artificial Neural Networks/010. Embeddings.mp4 21.4 MB
Chapter 3 The Neuron/005. The Neuron.mp4 21.1 MB
Chapter 4 Feedforward Artificial Neural Networks/002. Forward Propagation.mp4 21.0 MB
Chapter 6 Recurrent Neural Networks/003. Simple RNN Elman Unit (pt 2).mp4 20.7 MB

[磁力链接] 添加时间:2024-07-20 大小:934.1 MB 最近下载:2025-10-25 热度:5747

Packt Publishing - Deep Dive into Python Machine Learning

Project_Files/Python Machine Learning Solutions [Video].zip 60.6 MB
Project_Files/Deep Learning with Python [Video].zip 605.0 kB
Project_Files/Mastering Python - Second Edition [Video].zip 36.7 kB
Project_Files/Data Mining with Python- Implementing Classification and Regression.zip 17.2 kB
71 - Logistic Regression Model Implementation.mp4 49.5 MB
25 - Using concurrent.futures.mp4 49.0 MB
23 - Executing Other Programs with Subprocess.mp4 47.7 MB
67 - Regression Model Implementation to Predict Television Show Viewers.mp4 42.3 MB
18 - Getting the Most Out of docstrings 1 - PEP 257 and docutils.mp4 40.5 MB
72 - K – Nearest Neighbor Classifier Implementation.mp4 40.2 MB
66 - Basic Regression Model Implementation to Predict House Prices.mp4 37.6 MB
172 - Deep Learning Hello World! Classifying the MNIST Data.mp4 36.4 MB
45 - Using the Reactive Extensions for Python (RxPY).mp4 35.3 MB
175 - Optimizing a Simple Model in Pure Theano.mp4 35.2 MB
181 - Reusing Pre-trained Models in New Applications.mp4 33.4 MB
05 - Extensive Standard Library.mp4 32.7 MB
185 - Recurrent Networks –Training a Sentiment Analysis Model for Text.mp4 31.2 MB
51 - Interfacing with C Code Using Cython.mp4 28.7 MB
73 - Preprocessing Data Using Different Techniques.mp4 27.7 MB
178 - Convolutional and Pooling Layers.mp4 26.6 MB

[磁力链接] 添加时间:2017-02-11 大小:2.8 GB 最近下载:2025-10-25 热度:5728

[FreeCourseSite.com] Udemy - Complete Data Science & Machine Learning A-Z with Python

42. Competition Section on Kaggle/2. Competitions on Kaggle Lesson 2.mp4 201.0 MB
42. Competition Section on Kaggle/1. Competitions on Kaggle Lesson 1.mp4 197.3 MB
44. Code Section on Kaggle/3. Examining the Code Section in Kaggle Lesson 3.mp4 167.7 MB
43. Dataset Section on Kaggle/1. Datasets on Kaggle.mp4 139.7 MB
41. First Contact with Kaggle/1. What is Kaggle.mp4 136.0 MB
48. Introduction to Machine Learning with Real Hearth Attack Prediction Project/6. Recognizing Variables In Dataset.mp4 133.0 MB
41. First Contact with Kaggle/5. Getting to Know the Kaggle Homepage.mp4 128.9 MB
1. Installations/1. Installing Anaconda Distribution for Windows.mp4 124.1 MB
48. Introduction to Machine Learning with Real Hearth Attack Prediction Project/1. First Step to the Hearth Attack Prediction Project.mp4 122.8 MB
1. Installations/5. Installing Anaconda Distribution for Linux.mp4 120.3 MB
21. Matplotlib/8. Basic Plots in Matplotlib I.mp4 116.6 MB
46. Other Most Used Options on Kaggle/2. Ranking Among Users on Kaggle.mp4 112.2 MB
27. Linear Regression Algorithm in Machine Learning A-Z/3. Linear Regression Algorithm With Python Part 2.mp4 112.1 MB
44. Code Section on Kaggle/2. Examining the Code Section in Kaggle Lesson 2.mp4 111.0 MB
48. Introduction to Machine Learning with Real Hearth Attack Prediction Project/3. Notebook Design to be Used in the Project.mp4 110.0 MB
25. Evaluation Metrics in Machine Learning/2. Machine Learning Model Performance Evaluation Classification Error Metrics.mp4 105.1 MB
22. Seaborn/5. Basic Plots in Seaborn.mp4 103.6 MB
25. Evaluation Metrics in Machine Learning/4. Machine Learning With Python.mp4 96.7 MB
50. Preparation For Exploratory Data Analysis (EDA) in Data Science/4. Examining Statistics of Variables.mp4 95.8 MB
14. Functions That Can Be Applied on a DataFrame/3. Aggregation Functions in Pandas DataFrames.mp4 95.1 MB

[磁力链接] 添加时间:2023-12-17 大小:11.3 GB 最近下载:2025-10-25 热度:5692

Linkedin Learning Machine Learning With Python-Decision Trees

4. Working with Regression Trees/1. How to build a regression tree in Python.mp4 23.9 MB
2. Decision Trees/5. How to prune a decision tree.mp4 21.2 MB
4. Working with Regression Trees/3. How to prune a regression tree in Python.mp4 18.8 MB
3. Working with Classification Trees/1. How to build a classification tree in Python.mp4 18.6 MB
2. Decision Trees/3. How do classification trees measure impurity.mp4 16.1 MB
2. Decision Trees/2. How is a classification tree built.mp4 15.4 MB
2. Decision Trees/4. How is a regression tree built.mp4 15.1 MB
3. Working with Classification Trees/3. How to prune a classification tree in Python.mp4 14.8 MB
4. Working with Regression Trees/2. How to visualize a regression tree in Python.mp4 14.1 MB
3. Working with Classification Trees/2. How to visualize a classification tree in Python.mp4 13.2 MB
2. Decision Trees/1. What is a decision tree.mp4 13.0 MB
2. Decision Trees/6. Why and when to use a decision tree.mp4 10.4 MB
1. Introduction/4. Using the exercise files.mp4 5.5 MB
5. Conclusion/1. Next steps with decision trees.mp4 4.5 MB
1. Introduction/3. The tools you need.mp4 3.5 MB
1. Introduction/1. Making decisions with Python.mp4 3.4 MB
1. Introduction/2. What you should know.mp4 3.1 MB
Exercise Files/03/03e.ipynb 11.5 kB
Exercise Files/03/03b.ipynb 11.0 kB
4. Working with Regression Trees/1. How to build a regression tree in Python.srt 10.6 kB

[磁力链接] 添加时间:2024-08-24 大小:214.8 MB 最近下载:2025-10-26 热度:5674

Data Science Deep Learning and Neural Networks in Python

[TutsNode.com] - Data Science Deep Learning and Neural Networks in Python/11. Setting Up Your Environment (FAQ by Student Request)/1. Windows-Focused Environment Setup 2018.mp4 195.4 MB
[TutsNode.com] - Data Science Deep Learning and Neural Networks in Python/7. TensorFlow, exercises, practice, and what to learn next/1. TensorFlow plug-and-play example.mp4 105.7 MB
[TutsNode.com] - Data Science Deep Learning and Neural Networks in Python/10. Higher-Level Discussion/3. Who should learn backpropagation in 2020 and beyond.mp4 92.0 MB
[TutsNode.com] - Data Science Deep Learning and Neural Networks in Python/12. Extra Help With Python Coding for Beginners (FAQ by Student Request)/4. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
[TutsNode.com] - Data Science Deep Learning and Neural Networks in Python/5. Training a neural network/11. Backpropagation (part 3).mp4 77.0 MB
[TutsNode.com] - Data Science Deep Learning and Neural Networks in Python/5. Training a neural network/6. Training Logistic Regression with Softmax (part 1).mp4 62.5 MB
[TutsNode.com] - Data Science Deep Learning and Neural Networks in Python/10. Higher-Level Discussion/2. Who should take this course in 2020 and beyond.mp4 60.2 MB
[TutsNode.com] - Data Science Deep Learning and Neural Networks in Python/10. Higher-Level Discussion/4. Where does this course fit into your deep learning studies.mp4 56.7 MB
[TutsNode.com] - Data Science Deep Learning and Neural Networks in Python/5. Training a neural network/5. Categorical Cross-Entropy Loss Function.mp4 51.8 MB
[TutsNode.com] - Data Science Deep Learning and Neural Networks in Python/5. Training a neural network/10. Backpropagation in code.mp4 48.6 MB
[TutsNode.com] - Data Science Deep Learning and Neural Networks in Python/11. Setting Up Your Environment (FAQ by Student Request)/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.0 MB
[TutsNode.com] - Data Science Deep Learning and Neural Networks in Python/1. Welcome/3. How to Succeed in this Course.mp4 45.9 MB
[TutsNode.com] - Data Science Deep Learning and Neural Networks in Python/7. TensorFlow, exercises, practice, and what to learn next/2. Visualizing what a neural network has learned using TensorFlow Playground.mp4 45.3 MB
[TutsNode.com] - Data Science Deep Learning and Neural Networks in Python/5. Training a neural network/9. Backpropagation (part 2).mp4 44.1 MB
[TutsNode.com] - Data Science Deep Learning and Neural Networks in Python/13. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 40.8 MB
[TutsNode.com] - Data Science Deep Learning and Neural Networks in Python/2. Review/4. Neuron Training.mp4 40.4 MB
[TutsNode.com] - Data Science Deep Learning and Neural Networks in Python/1. Welcome/1. Introduction and Outline.mp4 39.7 MB
[TutsNode.com] - Data Science Deep Learning and Neural Networks in Python/14. Appendix FAQ Finale/2. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 39.7 MB
[TutsNode.com] - Data Science Deep Learning and Neural Networks in Python/13. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/5. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 39.4 MB
[TutsNode.com] - Data Science Deep Learning and Neural Networks in Python/5. Training a neural network/4. How to Brace Yourself to Learn Backpropagation.mp4 39.1 MB

[磁力链接] 添加时间:2022-01-30 大小:2.2 GB 最近下载:2025-10-25 热度:5625

[GigaCourse.Com] Udemy - Beginner Machine Learning in Python + ChatGPT Bonus [2023]

02 - Regression/008 Linear Regression Hands-On - Step 3.mp4 48.4 MB
02 - Regression/010 Linear Regression Hands-On - Step 4.mp4 36.4 MB
02 - Regression/007 Linear Regression Hands-On - Step 2.mp4 36.4 MB
03 - Classification/009 Logistic Regression Hands-On - Step 5.mp4 31.3 MB
04 - Clustering/011 K-Means Clustering - Step 5b.mp4 29.0 MB
03 - Classification/002 Logistic Regression.mp4 25.9 MB
02 - Regression/005 Assumptions of Linear Regression.mp4 25.8 MB
02 - Regression/006 Linear Regression Hands-On - Step 1.mp4 25.6 MB
03 - Classification/006 Logistic Regression Hands-On - Step 3.mp4 21.5 MB
03 - Classification/004 Logistic Regression Hands-On - Step 1.mp4 21.4 MB
01 - Introduction/005 A walk-through the course materials and Google Colab.mp4 20.9 MB
04 - Clustering/007 K-Means Clustering - Step 3b.mp4 20.8 MB
04 - Clustering/006 K-Means Clustering - Step 3a.mp4 19.4 MB
03 - Classification/012 Logistic Regression Hands-On - Step 8a.mp4 19.3 MB
04 - Clustering/010 K-Means Clustering - Step 5a.mp4 17.4 MB
04 - Clustering/004 K-Means Clustering - Step 1.mp4 17.1 MB
03 - Classification/014 Confusion Matrix and Accuracy.mp4 16.3 MB
04 - Clustering/001 What is Clustering.mp4 16.2 MB
03 - Classification/007 Logistic Regression Hands-On - Step 4.mp4 15.0 MB
04 - Clustering/009 K-Means Clustering - Step 4.mp4 14.9 MB

[磁力链接] 添加时间:2024-03-19 大小:728.3 MB 最近下载:2025-10-22 热度:5522

Machine Learning Fundamentals A Python-Based Course

Module 4 Supervised Learning Fundamentals/013. Lesson 4.13 Supervised Learning in Python.mp4 203.5 MB
Module 2 Mathematical Concepts of Machine Learning/003. Lesson 2.3 Matrices Basics.mp4 178.5 MB
Module 4 Supervised Learning Fundamentals/001. Lesson 4.1 Supervision in Machine Learning.mp4 173.8 MB
Module 4 Supervised Learning Fundamentals/014. Lesson 4.14 Introduction to Hyperparameter Optimization.mp4 171.6 MB
Module 5 Unsupervised Learning Fundamentals/005. Lesson 5.5 Unsupervised Learning in Python.mp4 171.2 MB
Module 4 Supervised Learning Fundamentals/002. Lesson 4.2 Introduction to Feature Engineering.mp4 169.6 MB
Module 4 Supervised Learning Fundamentals/012. Lesson 4.12 Decision Trees Basics.mp4 164.3 MB
Module 2 Mathematical Concepts of Machine Learning/001. Lesson 2.1 Introduction to the Mathematical Principles of Machine Learning.mp4 161.6 MB
Module 4 Supervised Learning Fundamentals/010. Lesson 4.10 Class Imbalance Problems.mp4 161.2 MB
Module 4 Supervised Learning Fundamentals/009. Lesson 4.9 Classification Metrics.mp4 153.7 MB
Module 4 Supervised Learning Fundamentals/007. Lesson 4.7 Linear Regression in Python - Testing the Assumptions.mp4 148.6 MB
Module 5 Unsupervised Learning Fundamentals/003. Lesson 5.3 k-Means Clustering.mp4 148.3 MB
Module 6 Machine Learning Applications/001. Lesson 6.1 Introduction to Natural Language Processing (NLP).mp4 140.0 MB
Module 4 Supervised Learning Fundamentals/004. Lesson 4.4 Linear Regression Basics - Closed-form solution.mp4 136.0 MB
Module 3 Statistical Concepts of Machine Learning/005. Lesson 3.5 Statistical Inference and Modeling Basics.mp4 135.6 MB
Module 3 Statistical Concepts of Machine Learning/001. Lesson 3.1 Introduction to the Statistical Principles of Machine Learning.mp4 133.7 MB
Module 2 Mathematical Concepts of Machine Learning/002. Lesson 2.2 Vectors.mp4 132.6 MB
Module 4 Supervised Learning Fundamentals/006. Lesson 4.6 Linear Regression in Python - Simple and Multivariate Regression.mp4 131.5 MB
Module 6 Machine Learning Applications/003. Lesson 6.3 Text Representation Methods - Part 2 TF-IDF Method.mp4 129.6 MB
Module 5 Unsupervised Learning Fundamentals/004. Lesson 5.4 Principal Component Analysis (PCA) Basics.mp4 125.7 MB

[磁力链接] 添加时间:2024-10-30 大小:4.5 GB 最近下载:2025-10-22 热度:5505

Natural Language Processing - Machine Learning Models in Python

Chapter 3 Spam Detection/006. Spam Detection in Python.mp4 56.1 MB
Chapter 5 Text Summarization/008. TextRank in Python (Advanced).mp4 40.9 MB
Chapter 5 Text Summarization/004. Text Summarization in Python.mp4 39.1 MB
Chapter 7 Latent Semantic Analysis (Latent Semantic Indexing)/002. SVD (Singular Value Decomposition) Intuition.mp4 38.7 MB
Chapter 6 Topic Modeling/006. Topic Modeling with Latent Dirichlet Allocation (LDA) in Python.mp4 36.6 MB
Chapter 4 Sentiment Analysis/002. Logistic Regression Intuition (pt 1).mp4 35.8 MB
Chapter 6 Topic Modeling/005. Latent Dirichlet Allocation (LDA) - Intuition (Advanced).mp4 33.1 MB
Chapter 4 Sentiment Analysis/006. Sentiment Analysis in Python (pt 1).mp4 31.0 MB
Chapter 3 Spam Detection/004. Aside Class Imbalance, ROC, AUC, and F1 Score (pt 1).mp4 30.6 MB
Chapter 6 Topic Modeling/002. Latent Dirichlet Allocation (LDA) - Essentials.mp4 28.0 MB
Chapter 3 Spam Detection/005. Aside Class Imbalance, ROC, AUC, and F1 Score (pt 2).mp4 28.0 MB
Chapter 3 Spam Detection/002. Naive Bayes Intuition.mp4 27.5 MB
Chapter 7 Latent Semantic Analysis (Latent Semantic Indexing)/004. Latent Semantic Analysis Latent Semantic Indexing in Python.mp4 27.4 MB
Chapter 6 Topic Modeling/007. Non-Negative Matrix Factorization (NMF) Intuition.mp4 26.1 MB
Chapter 5 Text Summarization/006. TextRank - How It Really Works (Advanced).mp4 25.9 MB
Chapter 4 Sentiment Analysis/007. Sentiment Analysis in Python (pt 2).mp4 24.9 MB
Chapter 5 Text Summarization/005. TextRank Intuition.mp4 22.3 MB
Chapter 5 Text Summarization/009. Text Summarization in Python - The Easy Way (Beginner).mp4 21.9 MB
Chapter 4 Sentiment Analysis/004. Logistic Regression Training and Interpretation.mp4 21.4 MB
Chapter 4 Sentiment Analysis/001. Sentiment Analysis - Problem Description.mp4 20.8 MB

[磁力链接] 添加时间:2024-07-23 大小:827.1 MB 最近下载:2025-10-26 热度:5480

[FreeCourseSite.com] Udemy - Machine Learning A-Z™ Python & R in Data Science [2023]

[FreeCourseSite.com] Udemy - Machine Learning A-Z™ Python & R in Data Science [2023].part1.rar 6.4 GB
[FreeCourseSite.com] Udemy - Machine Learning A-Z™ Python & R in Data Science [2023].part2.rar 6.4 GB
[FreeCourseSite.com] Udemy - Machine Learning A-Z™ Python & R in Data Science [2023].part3.rar 78.6 MB

[磁力链接] 添加时间:2023-12-21 大小:13.0 GB 最近下载:2025-10-22 热度:5453

Edureka - Practical Deep Learning With Python

03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/09-demonstration_next_word_prediction_model_compilation_and_prediction.mp4 101.3 MB
01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/09-demonstration_handwritten_digits_classification_optimizing_the_model.mp4 93.1 MB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/03-Faster_Rcnn_Recurrent_Convolutional_Neural_Network/05-demonstration_object_detection_with_faster_rcnn_building_the_model.mp4 86.9 MB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/11-demonstration_building_basic_cnn_model_with_new_parameters.mp4 82.0 MB
01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/13-single_layer_perceptron_decision_boundary.mp4 80.9 MB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/03-Faster_Rcnn_Recurrent_Convolutional_Neural_Network/04-demonstration_object_detection_with_faster_rcnn_pretrained_model_setup.mp4 78.3 MB
01-Deep_Learning_Components/03-Building_Perceptron_And_Its_Working/08-demonstration_handwritten_digits_classification_designing_the_model.mp4 76.8 MB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/10-demonstration_adding_more_layers.mp4 65.4 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/01-Working_Of_Recurrent_Neural_Networks_Rnn/06-demonstration_rnn_building_the_model.mp4 65.4 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/01-Working_Of_Recurrent_Neural_Networks_Rnn/05-demonstration_rnn_dataset_preparation.mp4 65.1 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/08-demonstration_next_word_prediction_layers.mp4 61.8 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/06-demonstration_model_compilation_preparing_the_dataset.mp4 58.2 MB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/02-Tensorflow_Hub_For_Object_Detection_Using_Faster_Rcnn/07-demonstration_training_the_model_and_visualizing_the_predictions.mp4 56.2 MB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/07-demonstration_designing_the_model.mp4 55.4 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/02-Lstm_Architecture/07-demonstration_next_word_prediction_processing_the_corpus.mp4 52.6 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/07-demonstration_building_and_compiling_model.mp4 48.5 MB
03-Deep_Learning_With_Rnn_Lstm_And_Model_Optimization/03-Module_Optimization_And_Compilation/08-demonstration_from_rmsprop_to_adam.mp4 47.4 MB
01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/12-single_layer_perceptron_define_sigmoid_function.mp4 46.1 MB
01-Deep_Learning_Components/02-Essentials_Of_Deep_Learning/03-neural_networks.mp4 44.2 MB
02-Deep_Learning_With_Cnn_Rcnn_And_Faster_Rcnn/01-Convolutional_Neural_Network/06-demonstration_load_and_preprocess_the_data.mp4 44.1 MB

[磁力链接] 添加时间:2025-03-03 大小:2.9 GB 最近下载:2025-10-25 热度:5406

[Udemy] Deep Learning Recurrent Neural Networks in Python (06.2021)

10. Setting Up Your Environment (FAQ by Student Request)/1. Windows-Focused Environment Setup 2018.mp4 323.9 MB
10. Setting Up Your Environment (FAQ by Student Request)/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 201.3 MB
5. Recurrent Neural Networks, Time Series, and Sequence Data/12. Demo of the Long Distance Problem.mp4 150.0 MB
12. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 142.9 MB
12. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 141.5 MB
11. Extra Help With Python Coding for Beginners (FAQ by Student Request)/3. Proof that using Jupyter Notebook is the same as not using it.mp4 113.7 MB
2. Google Colab/2. Uploading your own data to Google Colab.mp4 108.3 MB
5. Recurrent Neural Networks, Time Series, and Sequence Data/17. Stock Return Predictions using LSTMs (pt 3).mp4 104.2 MB
4. Feedforward Artificial Neural Networks/9. ANN for Regression.mp4 104.0 MB
5. Recurrent Neural Networks, Time Series, and Sequence Data/3. Autoregressive Linear Model for Time Series Prediction.mp4 102.7 MB
11. Extra Help With Python Coding for Beginners (FAQ by Student Request)/1. How to Code by Yourself (part 1).mp4 98.1 MB
5. Recurrent Neural Networks, Time Series, and Sequence Data/11. A More Challenging Sequence.mp4 92.5 MB
5. Recurrent Neural Networks, Time Series, and Sequence Data/7. RNN for Time Series Prediction.mp4 90.4 MB
3. Machine Learning and Neurons/5. Classification Notebook.mp4 81.4 MB
5. Recurrent Neural Networks, Time Series, and Sequence Data/8. Paying Attention to Shapes.mp4 79.9 MB
6. Natural Language Processing (NLP)/4. Text Classification with LSTMs.mp4 79.2 MB
2. Google Colab/1. Intro to Google Colab, how to use a GPU or TPU for free.mp4 75.0 MB
5. Recurrent Neural Networks, Time Series, and Sequence Data/1. Sequence Data.mp4 69.8 MB
3. Machine Learning and Neurons/11. How does a model learn.mp4 63.5 MB
12. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 63.1 MB

[磁力链接] 添加时间:2022-02-05 大小:3.9 GB 最近下载:2025-10-26 热度:5399

GetFreeCourses.Co-Udemy-Machine Learning A-Z™ Python & R in Data Science [2023]

41 - Kernel PCA/372 - Kernel PCA in R.mp4 418.7 MB
29 - Apriori/271 - Apriori in R Step 3.mp4 282.1 MB
36 - Artificial Neural Networks/339 - ANN in R Step 1.mp4 238.7 MB
37 - Convolutional Neural Networks/345 - dataset.zip 232.0 MB
36 - Artificial Neural Networks/341 - ANN in R Step 3.mp4 212.6 MB
20 - Naive Bayes/197 - Bayes Theorem.mp4 204.7 MB
29 - Apriori/268 - Apriori in Python Step 4.mp4 201.8 MB
43 - Model Selection/375 - Grid Search in Python.mp4 196.8 MB
37 - Convolutional Neural Networks/359 - CNN in Python FINAL DEMO.mp4 195.1 MB
35 - Part 8 Deep Learning/324 - What is Deep Learning.mp4 186.8 MB
39 - Principal Component Analysis PCA/365 - PCA in R Step 1.mp4 184.3 MB
37 - Convolutional Neural Networks/355 - CNN in Python Step 2.mp4 182.9 MB
40 - Linear Discriminant Analysis LDA/370 - LDA in R.mp4 173.3 MB
32 - Upper Confidence Bound UCB/287 - Upper Confidence Bound in R Step 3.mp4 172.7 MB
29 - Apriori/270 - Apriori in R Step 2.mp4 169.8 MB
44 - XGBoost/378 - XGBoost in Python.mp4 149.5 MB
37 - Convolutional Neural Networks/358 - CNN in Python Step 5.mp4 147.0 MB
37 - Convolutional Neural Networks/349 - Step 2 Pooling.mp4 146.2 MB
34 - Part 7 Natural Language Processing/307 - Natural Language Processing in Python Step 5.mp4 143.5 MB
39 - Principal Component Analysis PCA/363 - PCA in Python Step 1.mp4 143.0 MB

[磁力链接] 添加时间:2024-02-25 大小:17.4 GB 最近下载:2025-10-16 热度:5355