DataScience Algorithms Analysis

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1. Given a DataSet for analysis, you need to apply following DataScience Algorithms:

- Linear Regression

- Logical Regression,

- Support Vector Machine(SVM)

- K Nearest Neighbour(KNN)

- Random Variable

- Classification Method

2. Comparison of each algorithm after analysis and display the comparison results.

3. Design a model that predicts the crime rate for each kind of crime given the location. Create labels and classes

**NOTE: You may use Python libraries like sklearn for pre-processing and post-processing.

Ilmu Data Python

ID Proyek: #13694824

Tentang proyek

13 proposal Proyek online Aktif 6 tahun yang lalu

13 freelancer rata-rata menawar $57 untuk pekerjaan ini

vtatarenko

Hi there! I am a professional mathematician and algorithm implementer. I also have 3 years experience in python. You can view my profile to make sure that I am a right person. I would like to work on your project. Lebih banyak

$88 USD dalam 3 hari
(22 Ulasan)
4.9
dannyflorida

I have done similar projects before. I am new freelancer so please accept my lower than usual offer and lets discuss more on chat. I would like some more details to give an accurate time and budget estimation.

$25 USD dalam 1 hari
(10 Ulasan)
4.7
sushanthpakki

Hi. I have good command over machine learning algorithms and the sklearn python library.

$25 USD dalam 2 hari
(18 Ulasan)
3.7
Valuesolutions

Hello, how are you? I hope you have a bright day/evening from your side. I have read the details provided, but please contact me so that we can discuss more on the project. I believe I have the required skills in this Lebih banyak

$126 USD dalam 1 hari
(7 Ulasan)
4.9
akshaynaidu9

Hello, I am applying for this job because I've a keen interest in BigData technology and I’m considering your job post for me with the required capabilities. I have learned R programming, Hadoop and its componen Lebih banyak

$66 USD dalam 5 hari
(2 Ulasan)
1.7
sindhuee

Implemented all the algorithms on a part dataset

$35 USD dalam 2 hari
(0 Ulasan)
0.0