首页
磁力链接怎么用
한국어
English
日本語
简体中文
繁體中文
[Tutorialsplanet.NET] Udemy - Complete Data Science Training with Python for Data Analysis
文件类型
收录时间
最后活跃
资源热度
文件大小
文件数量
视频
2020-10-28 17:14
2024-8-14 05:43
137
1.91 GB
118
磁力链接
magnet:?xt=urn:btih:13f2a54c3007f7d6e34ce9e3cbb37beb7e3e747f
迅雷链接
thunder://QUFtYWduZXQ6P3h0PXVybjpidGloOjEzZjJhNTRjMzAwN2Y3ZDZlMzRjZTllM2NiYjM3YmViN2UzZTc0N2ZaWg==
二维码链接
种子下载(838888不存储任何种子文件)
种子下载线路1(迅雷)--推荐
种子下载线路2(比特彗星)
种子下载线路3(torcache)
3条线路均为国内外知名下载网站种子链接,内容跟本站无关!
相关链接
Tutorialsplanet
NET
Udemy
-
Complete
Data
Science
Training
with
Python
for
Data
Analysis
文件列表
1. Introduction to the Data Science in Python Bootcamp/1. What is Data Science.mp4
8.35MB
1. Introduction to the Data Science in Python Bootcamp/2. Introduction to the Course & Instructor.mp4
29.62MB
1. Introduction to the Data Science in Python Bootcamp/4. Introduction to the Python Data Science Tool.mp4
25.02MB
1. Introduction to the Data Science in Python Bootcamp/5. For Mac Users.mp4
10.22MB
1. Introduction to the Data Science in Python Bootcamp/6. Introduction to the Python Data Science Environment.mp4
40.32MB
1. Introduction to the Data Science in Python Bootcamp/7. Some Miscellaneous IPython Usage Facts.mp4
12.01MB
1. Introduction to the Data Science in Python Bootcamp/8. Online iPython Interpreter.mp4
7.73MB
1. Introduction to the Data Science in Python Bootcamp/9. Conclusion to Section 1.mp4
6.48MB
10. Unsupervised Learning in Python/1. Unsupervised Classification- Some Basic Ideas.mp4
6.17MB
10. Unsupervised Learning in Python/10. Principal Component Analysis (PCA)-Practical Implementation.mp4
9.06MB
10. Unsupervised Learning in Python/11. Conclusions to Section 10.mp4
5.49MB
10. Unsupervised Learning in Python/2. KMeans-theory.mp4
5.15MB
10. Unsupervised Learning in Python/3. KMeans-implementation on the iris data.mp4
19.54MB
10. Unsupervised Learning in Python/4. Quantifying KMeans Clustering Performance.mp4
9.57MB
10. Unsupervised Learning in Python/5. KMeans Clustering with Real Data.mp4
12.08MB
10. Unsupervised Learning in Python/6. How Do We Select the Number of Clusters.mp4
19.04MB
10. Unsupervised Learning in Python/7. Hierarchical Clustering-theory.mp4
10.23MB
10. Unsupervised Learning in Python/8. Hierarchical Clustering-practical.mp4
29.39MB
10. Unsupervised Learning in Python/9. Principal Component Analysis (PCA)-Theory.mp4
5.91MB
11. Supervised Learning/1. What is This Section About.mp4
24.88MB
11. Supervised Learning/10. knn-Classification.mp4
18.2MB
11. Supervised Learning/11. knn-Regression.mp4
8.38MB
11. Supervised Learning/12. Gradient Boosting-classification.mp4
15.04MB
11. Supervised Learning/13. Gradient Boosting-regression.mp4
10.9MB
11. Supervised Learning/14. Voting Classifier.mp4
9.53MB
11. Supervised Learning/15. Conclusions to Section 11.mp4
7.23MB
11. Supervised Learning/2. Data Preparation for Supervised Learning.mp4
28.28MB
11. Supervised Learning/3. Pointers on Evaluating the Accuracy of Classification and Regression Modelling.mp4
24MB
11. Supervised Learning/4. Using Logistic Regression as a Classification Model.mp4
20.64MB
11. Supervised Learning/5. RF-Classification.mp4
28.48MB
11. Supervised Learning/6. RF-Regression.mp4
23.63MB
11. Supervised Learning/7. SVM- Linear Classification.mp4
7.39MB
11. Supervised Learning/8. SVM- Non Linear Classification.mp4
5.12MB
11. Supervised Learning/9. Support Vector Regression.mp4
10.19MB
12. Artificial Neural Networks (ANN) and Deep Learning (DL)/1. Theory Behind ANN and DNN.mp4
22.56MB
12. Artificial Neural Networks (ANN) and Deep Learning (DL)/10. Specify the Activation Function.mp4
6.21MB
12. Artificial Neural Networks (ANN) and Deep Learning (DL)/11. H2O Deep Learning For Predictions.mp4
12MB
12. Artificial Neural Networks (ANN) and Deep Learning (DL)/12. Conclusions to Section 12.mp4
5.16MB
12. Artificial Neural Networks (ANN) and Deep Learning (DL)/2. Perceptrons for Binary Classification.mp4
10.05MB
12. Artificial Neural Networks (ANN) and Deep Learning (DL)/3. Getting Started with ANN-binary classification.mp4
8.46MB
12. Artificial Neural Networks (ANN) and Deep Learning (DL)/4. Multi-label classification with MLP.mp4
13.49MB
12. Artificial Neural Networks (ANN) and Deep Learning (DL)/5. Regression with MLP.mp4
9.02MB
12. Artificial Neural Networks (ANN) and Deep Learning (DL)/6. MLP with PCA on a Large Dataset.mp4
19.25MB
12. Artificial Neural Networks (ANN) and Deep Learning (DL)/8. Start with H20.mp4
12.12MB
12. Artificial Neural Networks (ANN) and Deep Learning (DL)/9. Default H2O Deep Learning Algorithm.mp4
8.23MB
13. Miscellaneous Lectures & Information/2. Read in Data from Online CSV.mp4
6.66MB
13. Miscellaneous Lectures & Information/3. Read Data from a Database.mp4
12.26MB
13. Miscellaneous Lectures & Information/4. Naive Bayes Classification.mp4
9.86MB
13. Miscellaneous Lectures & Information/5. Data Imputation.mp4
56.41MB
2. Introduction to Python Pre-Requisites for Data Science/2. Different Types of Data Used in Statistical & ML Analysis.mp4
9.36MB
2. Introduction to Python Pre-Requisites for Data Science/3. Different Types of Data Used Programatically.mp4
7.74MB
2. Introduction to Python Pre-Requisites for Data Science/4. Python Data Science Packages To Be Used.mp4
7.93MB
2. Introduction to Python Pre-Requisites for Data Science/5. Conclusions to Section 2.mp4
4.88MB
3. Introduction to Numpy/1. Numpy Introduction.mp4
8.7MB
3. Introduction to Numpy/10. Conclusion to Section 3.mp4
6.17MB
3. Introduction to Numpy/2. Create Numpy Arrays.mp4
20.91MB
3. Introduction to Numpy/3. Numpy Operations.mp4
36.71MB
3. Introduction to Numpy/4. Matrix Arithmetic and Linear Systems.mp4
15.83MB
3. Introduction to Numpy/5. Numpy for Basic Vector Arithmetric.mp4
11.75MB
3. Introduction to Numpy/6. Numpy for Basic Matrix Arithmetic.mp4
13.89MB
3. Introduction to Numpy/7. Broadcasting with Numpy.mp4
8.95MB
3. Introduction to Numpy/8. Solve Equations with Numpy.mp4
11.44MB
3. Introduction to Numpy/9. Numpy for Statistical Operation.mp4
14.95MB
4. Introduction to Pandas/1. Data Structures in Python.mp4
25.07MB
4. Introduction to Pandas/3. Read in CSV Data Using Pandas.mp4
15.32MB
4. Introduction to Pandas/4. Read in Excel Data Using Pandas.mp4
11.38MB
4. Introduction to Pandas/5. Reading in JSON Data.mp4
18.72MB
4. Introduction to Pandas/6. Read in HTML Data.mp4
51.31MB
4. Introduction to Pandas/7. Conclusion to Section 4.mp4
5.4MB
5. Data Pre-ProcessingWrangling/1. Rationale behind this section.mp4
8.11MB
5. Data Pre-ProcessingWrangling/10. Rank and Sort Data.mp4
24.32MB
5. Data Pre-ProcessingWrangling/11. Concatenate.mp4
23.74MB
5. Data Pre-ProcessingWrangling/12. Merging and Joining Data Frames.mp4
28.8MB
5. Data Pre-ProcessingWrangling/13. Conclusion to Section 5.mp4
5.39MB
5. Data Pre-ProcessingWrangling/2. Removing NAsNo Values From Our Data.mp4
19.29MB
5. Data Pre-ProcessingWrangling/3. Basic Data Handling Starting with Conditional Data Selection.mp4
14.85MB
5. Data Pre-ProcessingWrangling/4. Drop ColumnRow.mp4
15.7MB
5. Data Pre-ProcessingWrangling/5. Subset and Index Data.mp4
28MB
5. Data Pre-ProcessingWrangling/6. Basic Data Grouping Based on Qualitative Attributes.mp4
26.62MB
5. Data Pre-ProcessingWrangling/7. Crosstabulation.mp4
10.88MB
5. Data Pre-ProcessingWrangling/8. Reshaping.mp4
24.27MB
5. Data Pre-ProcessingWrangling/9. Pivoting.mp4
24.04MB
6. Introduction to Data Visualizations/1. What is Data Visualization.mp4
20.72MB
6. Introduction to Data Visualizations/2. Some Theoretical Principles Behind Data Visualization.mp4
16.56MB
6. Introduction to Data Visualizations/3. Histograms-Visualize the Distribution of Continuous Numerical Variables.mp4
29.41MB
6. Introduction to Data Visualizations/4. Boxplots-Visualize the Distribution of Continuous Numerical Variables.mp4
13.44MB
6. Introduction to Data Visualizations/5. Scatter Plot-Visualize the Relationship Between 2 Continuous Variables.mp4
29.82MB
6. Introduction to Data Visualizations/6. Barplot.mp4
53.81MB
6. Introduction to Data Visualizations/7. Pie Chart.mp4
12.8MB
6. Introduction to Data Visualizations/8. Line Chart.mp4
37.09MB
6. Introduction to Data Visualizations/9. Conclusions to Section 6.mp4
5.83MB
7. Statistical Data Analysis-Basic/1. What is Statistical Data Analysis.mp4
25.29MB
7. Statistical Data Analysis-Basic/10. Standard Normal Distribution and Z-scores.mp4
9.81MB
7. Statistical Data Analysis-Basic/11. Confidence Interval-Theory.mp4
13.72MB
7. Statistical Data Analysis-Basic/12. Confidence Interval-Calculation.mp4
13.65MB
7. Statistical Data Analysis-Basic/13. Conclusions to Section 7.mp4
3.82MB
7. Statistical Data Analysis-Basic/2. Some Pointers on Collecting Data for Statistical Studies.mp4
20.9MB
7. Statistical Data Analysis-Basic/4. Explore the Quantitative Data Descriptive Statistics.mp4
17.39MB
7. Statistical Data Analysis-Basic/5. Grouping & Summarizing Data by Categories.mp4
33.05MB
7. Statistical Data Analysis-Basic/6. Visualize Descriptive Statistics-Boxplots.mp4
11.5MB
7. Statistical Data Analysis-Basic/7. Common Terms Relating to Descriptive Statistics.mp4
11.6MB
7. Statistical Data Analysis-Basic/8. Data Distribution- Normal Distribution.mp4
9.6MB
7. Statistical Data Analysis-Basic/9. Check for Normal Distribution.mp4
16.47MB
8. Statistical Inference & Relationship Between Variables/1. What is Hypothesis Testing.mp4
13.41MB
8. Statistical Inference & Relationship Between Variables/10. Polynomial Regression.mp4
9.23MB
8. Statistical Inference & Relationship Between Variables/11. GLM Generalized Linear Model.mp4
11.84MB
8. Statistical Inference & Relationship Between Variables/12. Logistic Regression.mp4
28.78MB
8. Statistical Inference & Relationship Between Variables/13. Conclusions to Section 8.mp4
4.94MB
8. Statistical Inference & Relationship Between Variables/2. Test the Difference Between Two Groups.mp4
17.78MB
8. Statistical Inference & Relationship Between Variables/3. Test the Difference Between More Than Two Groups.mp4
28.28MB
8. Statistical Inference & Relationship Between Variables/4. Explore the Relationship Between Two Quantitative Variables.mp4
9.44MB
8. Statistical Inference & Relationship Between Variables/5. Correlation Analysis.mp4
20.73MB
8. Statistical Inference & Relationship Between Variables/6. Linear Regression-Theory.mp4
24.87MB
8. Statistical Inference & Relationship Between Variables/7. Linear Regression-Implementation in Python.mp4
30.15MB
8. Statistical Inference & Relationship Between Variables/8. Conditions of Linear Regression.mp4
2.98MB
8. Statistical Inference & Relationship Between Variables/9. Conditions of Linear Regression-Check in Python.mp4
33.36MB
9. Machine Learning for Data Science/1. How is Machine Learning Different from Statistical Data Analysis.mp4
13.71MB
9. Machine Learning for Data Science/2. What is Machine Learning (ML) About Some Theoretical Pointers.mp4
15.75MB
友情提示
不会用的朋友看这里 把磁力链接复制到离线下载,或者bt下载软件里即可下载文件,或者直接复制迅雷链接到迅雷里下载! 亲,你造吗?将网页分享给您的基友,下载的人越多速度越快哦!
违规内容投诉邮箱:
[email protected]
概述 838888磁力搜索是一个磁力链接搜索引擎,是学术研究的副产品,用于解决资源过度分散的问题 它通过BitTorrent协议加入DHT网络,实时的自动采集数据,仅存储文件的标题、大小、文件列表、文件标识符(磁力链接)等基础信息 838888磁力搜索不下载任何真实资源,无法判断资源的合法性及真实性,使用838888磁力搜索服务的用户需自行鉴别内容的真伪 838888磁力搜索不上传任何资源,不提供Tracker服务,不提供种子文件的下载,这意味着838888磁力搜索 838888磁力搜索是一个完全合法的系统