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# System prepended metadata

title: Untitled

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**introduction to machine learning (ethereum) with Omni Analytic Group.**
```
MODULE 3:
* Part 1: Always cool to give definitions of terms before using them, e.g (DDEMA), so its outline should come first before its expansive definition.
* Part 2:
    "learn how to find patterns in thes dataset with...."
    techniques to be used include: 
        -k-means (short defination or explanation of it will be nice),
        -Naming clusters (same as above).
(since each part kinda have distinct things they are to talk about, it'd be nice placing them as subtopics rather than an unordered list with the rest of the explanations).
so modelling as sub heading for part 2, ML techniques as suctions in the sub-heading.
part 3:
    -SL techniques: this involves using a "well" labelled dataset to....
    - techniques to be used includes:
        -glm, svm,...
A for action should be Part 4.
*Data injection not explained*

Page 4:
    -your turn (how about DIY?)
    -Asking questions of the data: question not clear, maybe rephrase?
    "T-test" 

Page 5: 
    -I'd suggest some "Read in data intro", to make it explainable, for instance, the library used, location of the dataset and a line data description.

Page 7:
    - what is written is all aboout assigning data types?
    
Page 10:
    - Short explanation of what skimr is.
    
Page 14:
    - old syntax exists, it'd be cool indicating "new syntax"
    
page 16:
    - Writing out the question will be nice (same as other questions before it).
    
page 20: 
    - visualization needs to be reworked, as some values (names or so) are lumped up.
    

```

**UNSUPERVISED LEARNING**
```
Title should probably include the **Modelling** part, since UL was said to be a sub-section in the modelling part of DDEMA.

page 2:
    - Group? (how about a more technical term -> "cluster")?

page 4:
    - ...we try to use Unsupervised techniques to find patterns within the dataset.

page 6: 
    - by grouping, it means clustering (for clarity of terms).
    - the pseudocode for the algorithm is as follows:
    
page 7:
    - Define TODO SSE
    
page 10:
    - ...so that we can compare "Proportions"
    
Page 12:
    - xaxis and yaxis labels can be such that it reflects the dataset been analyzed.
    
Page 14:
    - Screenshot of visualization can be re-scaled, some parts are cut off.

    
```

**SUPERVISED LEARNING**
```
page 2:
    - What we should cover and "we will cover"? kindly rephrase for better understanding.
    
page 4:
    - These pages are listed in the link below. "paste link here".
    -Tidyverse not spoken about?
    
page 5:
    - We are provided with data from a survey of....
    - an "observation" as to the class of owns_ethereum (either TRUE or FLASE).
    
page 6:
    - Some codes missing in the tale end of the page, needs rescaling maybe?
    
page 7:
    - Rescale visualization
    
page 9:
    - rephrase ":As an example"
    
page 11:
    - "e.g" accuracy, maybe some other metrics, recall?
    
page 14 & 15:
    - rescale to make all codes visible

```