├── LICENSE
├── README.md
├── TR Version
├── 1. Gün.pptx
├── 2. Gün.pptx
├── 3. Gün.pptx
├── Day-1.ipynb
├── Day-2.ipynb
├── Day-3.ipynb
├── Müfredat.docx
└── datasets
│ ├── Melbourne_housing.csv
│ └── airbnb_nyc_final.csv
└── assets
├── 1.png
├── 2.png
└── logo.png
/LICENSE:
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1 | MIT License
2 |
3 | Copyright (c) 2021 Global AI Hub
4 |
5 | Permission is hereby granted, free of charge, to any person obtaining a copy
6 | of this software and associated documentation files (the "Software"), to deal
7 | in the Software without restriction, including without limitation the rights
8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
9 | copies of the Software, and to permit persons to whom the Software is
10 | furnished to do so, subject to the following conditions:
11 |
12 | The above copyright notice and this permission notice shall be included in all
13 | copies or substantial portions of the Software.
14 |
15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21 | SOFTWARE.
22 |
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/README.md:
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1 |
6 |
7 | # 🎓 Data Analysis and Model Training Course by [Global AI Hub](https://globalaihub.com/community)
8 |
9 | # Syllabus:
10 |
11 | ### Day 1
12 | - What is `Data`?
13 | - Multimedia
14 | - Structured and Unstructured Data
15 | - Data Types
16 |
17 | - Data Visualization
18 | - What is Visualization?
19 | - Tufte's 6 Principle
20 | - Visualization Types
21 | - Line Plot
22 | - Scatter Plot
23 | - Bar Plot
24 | - Histogram
25 | - Pie Charts
26 | - Heatmap
27 | - Box Plot
28 | - Kartil Nedir? Nasıl Hesaplanır?
29 | - Joint Plot
30 | - KDE(Kernel Density Estimate)
31 |
32 | - Statistics
33 | - Descriptive Statistics Concepts
34 | - The Concept of Skewness
35 | - Correlation and Correlation Matrix
36 | - The Simpsons Paradox
37 | - Anscombe Quartet
38 | - Data Distribution and Hypothesis Testing
39 |
40 | - Data Distribution
41 | - Data and Distribution
42 | - Gaussian(Normal) Distribution
43 | - t-Distribution
44 | - Degrees of Freedom
45 | - Bernoulli's Distribution
46 | - Exponential Distribution
47 |
48 | - Application
49 | - Pandas Revision
50 | - Introduction to Data Preprocessing with Pandas
51 |
52 | ### Day 2
53 | - Hypothesis Tests
54 | - Basic Hypothesis testing
55 | - P value
56 | - T test
57 | - Z test
58 | - Chi-square (Chi-Square) Test
59 | - Errors in Hypothesis Testing
60 |
61 | - Data Cleaning
62 | - The 68-95-99.7 Rule and 3 Sigma
63 | - Outlier, Missing and Duplicate Data and their Detection
64 | - Z-Score
65 | - Handling missing values
66 | - Null vs NaN
67 | - Pandas Functions for missing values
68 | - Dimensionality Reduction
69 | - PCA (Principal Component Analysis)
70 | - Collinearity (Multiple Linear Connection
71 |
72 | - Data Transformation
73 | - Data Conversion Techniques
74 | - round
75 | - Scaling
76 | - Label Encoding
77 | - One Hot Encoding
78 | - Stack
79 | - melt
80 | - Shorts
81 | - Feature Engineering
82 |
83 | - Data Augmentation
84 | - Aggregation Functions
85 |
86 | - Application
87 | - Data Visualization with Seaborn
88 | - Data Preprocessing with Pandas
89 |
90 |
91 | ### Day 3
92 | - ML Review
93 | - What is Machine Learning?
94 | - Supervised Learning
95 | - Unsupervised Learning
96 | - Errors That May Be Encountered in Model Training
97 | - Tools Used in Data Analysis and Machine Learning
98 | - End-to-End Machine Learning Project Steps
99 |
100 | - Application
101 | - Training An End-to-End ML Model with a Real Dataset
102 |
103 | # Certification
104 | The course completion is certified.
105 |
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/TR Version/1. Gün.pptx:
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/TR Version/3. Gün.pptx:
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/TR Version/Müfredat.docx:
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/assets/logo.png:
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https://raw.githubusercontent.com/gaih/data-analysis/450cd0b2888a0e6285d46f0cbae40bff9754e3e2/assets/logo.png
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