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Shubam Sumbria

This is Python based Exploratory Data Analysis on traffic dataset to find out different trends in order to reduce traffic violations.

This dataset contains around 65k+ traffic related violation records.

Attribute Information:
1. stop_date - Date of violation
2. stop_time - Time of violation
3. driver_gender - Gender of violators (Male-M, Female-F)
4. driver_age - Age of violators
5. driver_race - Race of violators
6. violation - Category of violation :
- Speeding
- Moving Violation (Reckless driving, Hit and run, Assaulting another driver, pedestrian, improper turns and lane changes etc)
- Equipment (Window tint violations, Headlight/taillights out, Loud exhaust, Cracked windshield, etc.)
- Registration/Plates
- Seat Belt
- other (Call for…


Breast Cancer Wisconsin (Diagnostic) Dataset — Exploratory Data Analysis

Data Set Information:

Features are computed from a digitized image of a fine needle aspirate (FNA) of a breast mass. They describe characteristics of the cell nuclei.

Separating plane described above was obtained using Multi-surface Method-Tree (MSM-T) [K. P. Bennett, “Decision Tree Construction Via Linear Programming.” Proceedings of the 4th Midwest Artificial Intelligence and Cognitive Science Society, pp. 97–101, 1992], a classification method which uses linear programming to construct a decision tree. Relevant features were selected using an exhaustive search in the space of 1–4 features and 1–3 separating planes.

The actual linear program used to get the separating plane…


Statlog Heart Disease dataset (UCI Repository) — Exploratory Data Analysis

About Dataset:

This dataset is a heart disease database similar to a database already present in the repository (Heart Disease databases) but in a slightly different form.

Creators:

Hungarian Institute of Cardiology. Budapest: Andras Janosi, M.D.

University Hospital, Zurich, Switzerland: William Steinbrunn, M.D.

University Hospital, Basel, Switzerland: Matthias Pfisterer, M.D.

V.A. Medical Center, Long Beach and Cleveland Clinic Foundation: Robert Detrano, M.D., Ph.D.

Donor:
David W. Aha (aha ‘@’ ics.uci.edu) (714) 856–8779

Check UCI Machine Learning Repository for more heart Disease dataset.

Attribute Information:


⚡“Driving India Towards a Greener Future”

India has a lot to gain from the widespread adoption of e-mobility. Under the Make In India programme, the manufacturing of e-vehicles and their associated components is expected to increase the share of manufacturing in India’s GDP to 25% by 2022. On the economic front, large-scale adoption of electric vehicles is projected to help save $60 billion on oil imports by 2030 — currently 82% of India’s oil demand is fulfilled by imports. Price of electricity as fuel could fall as low as ₹1.1/km, helping an electric vehicle owner save up to ₹ 20,000 for every 5,000km traversed. …


Cleveland Heart Disease dataset (UCI Repository) — Exploratory Data Analysis

Data set dates from 1988 and comprises four databases: Cleveland, Hungary, Switzerland, and Long Beach V. It contains 76 attributes, including the predicted attribute, but all published experiments refer to using a subset of 14 of them. The “target” field refers to the presence of heart disease in the patient. It is integer valued 0 = disease and 1 = no disease.

Creators:

Hungarian Institute of Cardiology. Budapest: Andras Janosi, M.D.

University Hospital, Zurich, Switzerland: William Steinbrunn, M.D.

University Hospital, Basel, Switzerland: Matthias Pfisterer, M.D.

V.A. Medical Center, Long Beach and Cleveland Clinic Foundation: Robert Detrano, M.D., Ph.D.

Donor:
David W…


A short introduction about PyTorch and its functions.

PyTorch is an optimized tensor library for deep learning using GPUs and CPUs.

Used Functions:

  • torch.cat()
  • torch.split()
  • torch.hstack()
  • torch.vstack()
  • torch.transpose()

In this notebook, I Explained 5 different functions with 3 respectively examples and 1 of them is an example that “breaks” the function:

  1. cat( Concatenates the given sequence of seq tensors in the given dimension. All tensors must either have the same shape (except in the concatenating dimension) or be empty.)

Syntax:

  • torch.cat(tensors, dim=0, *, out=None)

Parameters:

  • tensors (sequence of Tensors) - any python sequence of tensors of the same type. Non-empty…

Shubam Sumbria

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