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【压缩文件】 Packt - Python Machine Learning Tips Tricks and Techniques

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Exercise Files/code_33873.zip 283.4 MB
5.Boost Your Overall Model Robustness/24.Perform Metric Selection on Real Data.mp4 64.2 MB
2.Feature Improvement with Non Linear Classification Techniques/08.Implementing kNN on the Data Set.mp4 30.9 MB
3.Power of Ensemble Learning with Python/13.Gradient Boosting Trees and Bayes Optimization.mp4 30.1 MB
3.Power of Ensemble Learning with Python/16.Implement Stacking.mp4 29.7 MB
1.Improving Your Models Using Feature Engineering/02.Using Feature Scaling to Standardize Data.mp4 28.0 MB
4.Recommender Systems/19.Applying Matrix Factorization on Datasets.mp4 24.8 MB
2.Feature Improvement with Non Linear Classification Techniques/09.Decision Tree as Predictive Model.mp4 24.5 MB
3.Power of Ensemble Learning with Python/15.Implement Blending.mp4 24.4 MB
3.Power of Ensemble Learning with Python/12.Random Forest for Classification.mp4 21.5 MB
2.Feature Improvement with Non Linear Classification Techniques/07.Support Vector Machines.mp4 20.7 MB
4.Recommender Systems/17.Memory-Based Collaborative Filtering.mp4 19.7 MB
2.Feature Improvement with Non Linear Classification Techniques/11.Combining All Together.mp4 19.6 MB
4.Recommender Systems/18.Item-to-Item Recommendation with kNN.mp4 19.3 MB
4.Recommender Systems/20.Wordbatch for Real-World Problem.mp4 19.2 MB
2.Feature Improvement with Non Linear Classification Techniques/10.Tricks with Dimensionality Reduction.mp4 18.9 MB
3.Power of Ensemble Learning with Python/14.CatBoost to Handle Categorical Data.mp4 17.9 MB
1.Improving Your Models Using Feature Engineering/04.Extracting Data with Feature Selection and Interaction.mp4 17.3 MB
5.Boost Your Overall Model Robustness/21.Validation Dataset Tuning.mp4 14.5 MB
1.Improving Your Models Using Feature Engineering/06.Build Model Based on Real-World Problems.mp4 13.2 MB

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02.Garbage-Collection-Tools/04.Using-VisualVM-and-VisualGC.mp4 35.1 MB
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03.Java-Reference-Classes/06.Using-PhantomReference.mp4 16.1 MB
00.Introduction/05.Demonstrating-How-the-Garbage-Collection-Works.mp4 15.6 MB
02.Garbage-Collection-Tools/02.Using-jstat.mp4 14.9 MB
02.Garbage-Collection-Tools/03.Using-jstat-to-Examine-the-Garbage-Collector.mp4 13.8 MB
03.Java-Reference-Classes/04.Using-WeakHashMap.mp4 11.3 MB
01.How-Garbage-Collection-Works-in-the-Oracle-JVM/05.Serial-Versus-Parallel-Garbage-Collectors.mp4 9.8 MB
03.Java-Reference-Classes/02.Using-WeakReference.mp4 9.5 MB
02.Garbage-Collection-Tools/01.Using-MX-Beans-to-to-Garbage-Collection-Data.mp4 8.3 MB
01.How-Garbage-Collection-Works-in-the-Oracle-JVM/04.What-Is-a-Cardtable-and-How-Is-It-Used-in-Garbage-Collection.mp4 6.6 MB
01.How-Garbage-Collection-Works-in-the-Oracle-JVM/02.Minor-Garbage-Collects-and-Major-Garbage-Collects.mp4 6.0 MB
00.Introduction/00.Course-Introduction.mp4 5.2 MB
03.Java-Reference-Classes/00.Introduction-to-Java-Reference-Types.mp4 5.1 MB
03.Java-Reference-Classes/03.How-Different-Reference-Types-Used-in-Your-Code.mp4 4.4 MB
01.How-Garbage-Collection-Works-in-the-Oracle-JVM/01.The-Basics-of-Garbage-Collection-in-the-Java-Virtual-Machine.mp4 4.2 MB
00.Introduction/03.Mark-and-Sweep-Garbage-Collection.mp4 3.1 MB
00.Introduction/01.Different-Types-of-Garbage-Collection.mp4 2.8 MB
01.How-Garbage-Collection-Works-in-the-Oracle-JVM/06.The-G1-Garbage-Collector.mp4 2.6 MB
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4. Conceitos fundamentais de Machine Learning e AI/2. Prevendo preços de apartamentos usando Machine Learning/12. Comparando Modelos.mp4 824.4 MB
1. PYTHON STARTER/3. Fundamentos da Linguagem/22. Solução dos exercícios - Parte 2.mp4 824.3 MB
1. PYTHON STARTER/1. Lógica de Programação/3. Algoritmos 2.mp4 804.8 MB
4. Conceitos fundamentais de Machine Learning e AI/2. Prevendo preços de apartamentos usando Machine Learning/4. Análise exploratória dos dados.mp4 792.7 MB
1. PYTHON STARTER/4. Projetos - Calculadora e software de gestão/2. Resolução - Calculadora.mp4 772.2 MB
1. PYTHON STARTER/5. Gerenciamento de erros e Depuração de código/6. Projeto Papel pedra e Tesoura.mp4 756.7 MB
9. Unsupervised Learning/1. Os modelos de aprendizado não supervisionado/9. Gaussian Mixture Models na Prática.mp4 746.9 MB
4. Conceitos fundamentais de Machine Learning e AI/2. Prevendo preços de apartamentos usando Machine Learning/10. Treinando os primeiros modelos.mp4 744.7 MB
5. Matemática para Data Science e Machine Learning/3. Álgebra Linear/2. O surgimento da algebra linear.mp4 724.1 MB
1. PYTHON STARTER/1. Lógica de Programação/2. Algoritmos 1.mp4 665.1 MB
2. Analisando Dados com Pandas/1. Conceitos básicos de Pandas/14. Entrada e Saída de dados.mp4 652.4 MB
1. PYTHON STARTER/4. Projetos - Calculadora e software de gestão/5. Resolução - Software de gestão para locadora de carros - Pt2.mp4 651.2 MB
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4. Conceitos fundamentais de Machine Learning e AI/1. Uma visão geral sobre Machine Learning e AI/7 - Conceitos Fundamentais de Machine Learning e Inteligência Artificial.mp4 604.8 MB
2. Analisando Dados com Pandas/1. Conceitos básicos de Pandas/4. Series.mp4 603.3 MB
4. Conceitos fundamentais de Machine Learning e AI/1. Uma visão geral sobre Machine Learning e AI/5 - Conceitos Fundamentais de Machine Learning e Inteligência Artificial.mp4 600.9 MB
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【压缩文件】 [ FreeCourseWeb.com ] Udemy - Machine Learning No-Code Approach - Using Azure ML Studio.zip

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【文档书籍】 15 free books on machine learning 2014-08-13

收录时间:2020-03-02 文档个数:76 文档大小:95.6 MB 最近下载:2025-02-11 人气:3500 磁力链接

04of15 - Bayesian Reasoning and Machine Learning.pdf 16.2 MB
06of15 - The Elements of Statistical Learning - Data Mining, Inference, and Prediction.pdf 12.8 MB
15of15 - Information Theory, Inference, and Learning Algorithms.pdf 11.7 MB
01of15 - [ONLY SAMPLE CHAPTERS 1-6] The LION Way - Machine Learning plus Intelligent Optimization/01of01 - Sample Chapters 1-6.pdf 6.7 MB
09of15 - Reinforcement Learning - An Introduction.pdf 5.5 MB
02of15 - A Course in Machine Learning.pdf 3.0 MB
12of15 - Introduction To Machine Learning.pdf 1.9 MB
11of15 - Machine Learning, Neural and Statistical Classification.pdf 1.8 MB
13of15 - Inductive Logic Programming - Techniques and Applications/01of01 - Complete Text.pdf 1.7 MB
07of15 - Reinforcement Learning/13of20 - Linear Subspace Learning for Facial Expression Analysis.pdf 1.4 MB
14of15 - Practical Artificial Intelligence Programming in Java.pdf 1.3 MB
07of15 - Reinforcement Learning/05of20 - Similarity Discriminant Analysis.pdf 1.3 MB
07of15 - Reinforcement Learning/06of20 - Forced Information for Information-Theoretic Competitive Learning.pdf 1.1 MB
07of15 - Reinforcement Learning/20of20 - Machine Learning for Sequential Behavior Modeling and Prediction.pdf 988.9 kB
07of15 - Reinforcement Learning/01of20 - Neural Machine Learning Approaches Q-Learning and Complexity Estimation Based Information Processing System.pdf 979.3 kB
07of15 - Reinforcement Learning/15of20 - 3D Shape Classification and Retrieval Using Heterogenous Features and Supervised Learning.pdf 906.7 kB
07of15 - Reinforcement Learning/10of20 - Learning Optimal Web Service Selections in Dynamic Environments when Many Quality-of-Service Criteria Matter.pdf 885.8 kB
10of15 - Gaussian Processes for Machine Learning/05of15 - Model Selection and Adaptation of Hyperparameters.pdf 862.9 kB
07of15 - Reinforcement Learning/16of20 - Performance Analysis of Hybrid Non-Supervised & Supervised Learning Techniques Applied to the Classification of Faults in Energy Transport Systems.pdf 824.3 kB
10of15 - Gaussian Processes for Machine Learning/03of15 - Classification.pdf 815.7 kB

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