Total words: 2027 | 2-word phrases: 529 | 3-word phrases: 606 | 4-word phrases: 626
PAGE INFO
Title | Try to keep the title under 60 characters (64 characters) The Basic Concepts of Data Science Explained | All Data Sciences |
Description | Try to keep the meta description between 50 - 160 characters (141 characters) An explanation of Data Science’s basic concepts and applications. It includes Artificial Intelligence, Machine Learning, and Deep Learning. |
Keywords | Meta keywords are not recommended anymore (0 characters)
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H1 | H1 tag on the page (30 characters) Basic Concepts of Data Science |
ONE WORD PHRASES 266 Words
# |
Keyword |
H1 |
Title |
Des |
Volume |
Position |
Suggest |
Frequency |
Density |
1 | data | | | | | | | 44 | 16.54% |
2 | and | | | | | | | 38 | 14.29% |
3 | the | | | | | | | 36 | 13.53% |
4 | science | | | | | | | 26 | 9.77% |
5 | of | | | | | | | 26 | 9.77% |
6 | is | | | | | | | 24 | 9.02% |
7 | a | | | | | | | 19 | 7.14% |
8 | to | | | | | | | 15 | 5.64% |
9 | learning | | | | | | | 10 | 3.76% |
10 | are | | | | | | | 10 | 3.76% |
TWO WORD PHRASES 529 Words
# |
Keyword |
H1 |
Title |
Des |
Volume |
Position |
Suggest |
Frequency |
Density |
1 | data science | | | | | | | 29 | 5.48% |
2 | science and | | | | | | | 9 | 1.70% |
3 | of data | | | | | | | 7 | 1.32% |
4 | and a | | | | | | | 6 | 1.13% |
5 | is a | | | | | | | 6 | 1.13% |
6 | of a | | | | | | | 6 | 1.13% |
7 | the model | | | | | | | 5 | 0.95% |
8 | it is | | | | | | | 5 | 0.95% |
9 | deep learning | | | | | | | 5 | 0.95% |
10 | is the | | | | | | | 5 | 0.95% |
11 | data sciences | | | | | | | 4 | 0.76% |
12 | artificial intelligence | | | | | | | 4 | 0.76% |
13 | a model | | | | | | | 4 | 0.76% |
14 | concepts of | | | | | | | 4 | 0.76% |
15 | all data | | | | | | | 4 | 0.76% |
16 | machine learning | | | | | | | 4 | 0.76% |
17 | and the | | | | | | | 3 | 0.57% |
18 | features are | | | | | | | 3 | 0.57% |
19 | model is | | | | | | | 3 | 0.57% |
20 | the data | | | | | | | 3 | 0.57% |
THREE WORD PHRASES 606 Words
# |
Keyword |
H1 |
Title |
Des |
Volume |
Position |
Suggest |
Frequency |
Density |
1 | data science and | | | | | | | 9 | 1.49% |
2 | concepts of data | | | | | | | 4 | 0.66% |
3 | of data science | | | | | | | 4 | 0.66% |
4 | all data sciences | | | | | | | 4 | 0.66% |
5 | basic concepts of | | | | | | | 3 | 0.50% |
6 | on the other | | | | | | | 2 | 0.33% |
7 | science and big | | | | | | | 2 | 0.33% |
8 | science with python | | | | | | | 2 | 0.33% |
9 | science and artificial | | | | | | | 2 | 0.33% |
10 | and artificial intelligence | | | | | | | 2 | 0.33% |
11 | data science is | | | | | | | 2 | 0.33% |
12 | science and economics | | | | | | | 2 | 0.33% |
13 | and big data | | | | | | | 2 | 0.33% |
14 | science and engineering | | | | | | | 2 | 0.33% |
15 | data science tools | | | | | | | 2 | 0.33% |
16 | science tools and | | | | | | | 2 | 0.33% |
17 | tools and techniques | | | | | | | 2 | 0.33% |
18 | machine learning is | | | | | | | 2 | 0.33% |
19 | data science universities | | | | | | | 2 | 0.33% |
20 | data science algorithms | | | | | | | 2 | 0.33% |
21 | are deduced from | | | | | | | 2 | 0.33% |
22 | data science with | | | | | | | 2 | 0.33% |
23 | it is used | | | | | | | 2 | 0.33% |
24 | and it is | | | | | | | 2 | 0.33% |
25 | the other hand | | | | | | | 2 | 0.33% |
26 | a model is | | | | | | | 2 | 0.33% |
27 | is used to | | | | | | | 2 | 0.33% |
28 | training set is | | | | | | | 1 | 0.17% |
29 | set is fed | | | | | | | 1 | 0.17% |
30 | is the process | | | | | | | 1 | 0.17% |
FOUR WORD PHRASES 626 Words
# |
Keyword |
H1 |
Title |
Des |
Volume |
Position |
Suggest |
Frequency |
Density |
1 | concepts of data science | | | | | | | 4 | 0.64% |
2 | basic concepts of data | | | | | | | 3 | 0.48% |
3 | data science and artificial | | | | | | | 2 | 0.32% |
4 | data science tools and | | | | | | | 2 | 0.32% |
5 | data science and economics | | | | | | | 2 | 0.32% |
6 | science and big data | | | | | | | 2 | 0.32% |
7 | data science and big | | | | | | | 2 | 0.32% |
8 | data science with python | | | | | | | 2 | 0.32% |
9 | data science and engineering | | | | | | | 2 | 0.32% |
10 | science and artificial intelligence | | | | | | | 2 | 0.32% |
11 | on the other hand | | | | | | | 2 | 0.32% |
12 | science tools and techniques | | | | | | | 2 | 0.32% |
13 | other hand training is | | | | | | | 1 | 0.16% |
14 | the basic concepts of | | | | | | | 1 | 0.16% |
15 | hand training is the | | | | | | | 1 | 0.16% |
16 | training is the process | | | | | | | 1 | 0.16% |
17 | of generating a model | | | | | | | 1 | 0.16% |
18 | generating a model from | | | | | | | 1 | 0.16% |
19 | a model from the | | | | | | | 1 | 0.16% |
20 | the other hand training | | | | | | | 1 | 0.16% |
21 | raw form on the | | | | | | | 1 | 0.16% |
22 | form on the other | | | | | | | 1 | 0.16% |
23 | or raw form on | | | | | | | 1 | 0.16% |
24 | form or raw form | | | | | | | 1 | 0.16% |
25 | organized form or raw | | | | | | | 1 | 0.16% |
26 | can be in an | | | | | | | 1 | 0.16% |
27 | data can be in | | | | | | | 1 | 0.16% |
28 | data data can be | | | | | | | 1 | 0.16% |
29 | of data data can | | | | | | | 1 | 0.16% |
30 | form of data data | | | | | | | 1 | 0.16% |
31 | any form of data | | | | | | | 1 | 0.16% |
32 | of any form of | | | | | | | 1 | 0.16% |
33 | collection of any form | | | | | | | 1 | 0.16% |
34 | the collection of any | | | | | | | 1 | 0.16% |
35 | is the collection of | | | | | | | 1 | 0.16% |
36 | dataset is the collection | | | | | | | 1 | 0.16% |
37 | model from the data | | | | | | | 1 | 0.16% |
38 | data using various algorithms | | | | | | | 1 | 0.16% |
39 | from the data using | | | | | | | 1 | 0.16% |
40 | model can recognize patterns | | | | | | | 1 | 0.16% |
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