-
**Is your feature request related to a problem? Please describe.**
This project aims to predict the stock prices of Netflix using various machine learning techniques. Historical stock data is utilize…
-
Full Name: Suvodeep Das
GitHub Profile Link:Â https://github.com/Suvodeep-Das
Objective: Creating a model to and testing accuracy using different algorithms(Random Forest, Logistic Regression, Decisi…
-
🌟 **Is your feature request related to a problem?**:
Thus preventing Heart diseases has become more than necessary. Good data-driven systems for predicting heart diseases can improve the entire resea…
-
Try out the following models on the data provided and document the results:
- K-Nearest Neighbor
- Random Forest
- Logistic Regression
Every model has to be in a `.py` file within models dir u…
-
We have a rich set of examples covering a very broad range of issues, but they're not necessarily easily discoverable via the section on the bottom of the API pages.
This meta-issue is to keep trac…
-
The script now only supports training and testing given an input dataset, we need to add a new function to support prediction given a new example.
- Save the trained models (doc2vec, random forest/…
-
I was able to successfully apply this method to a practical classification problem and got pretty good results.
However, when I try to use the default setup for a regression random forest in Python (…
-
The goal of this task is to create a model that can accurately predict the species of an iris flower based on its sepal length, sepal width, petal length, and petal width.
-
## Data Exploration
- [x] show initial balance of gender and race of raw data
## Pre-processing
- [x] create dataframes
- [ ] create different balanced/imbalanced data sets
- [x] combine indian…
-
The following case should be an error: train a model on some data then call `predict` with completely unrelated data (i.e. no features in common with the training set).
All of turicreate's regress…