{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "\n", " \n", "## [mlcourse.ai](mlcourse.ai) – Open Machine Learning Course \n", "###
Author: Name as in the rating, ODS Slack nickname\n", " \n", "##
Individual data analysis project" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Research plan**\n", " - Dataset and features description\n", " - Exploratory data analysis\n", " - Visual analysis of the features\n", " - Patterns, insights, pecularities of data\n", " - Data preprocessing\n", " - Feature engineering and description\n", " - Cross-validation, hyperparameter tuning\n", " - Validation and learning curves\n", " - Prediction for hold-out and test samples\n", " - Model evaluation with metrics description\n", " - Conclusions" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Part 1. Dataset and features description" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Part 2. Exploratory data analysis" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Part 3. Visual analysis of the features" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Part 4. Patterns, insights, pecularities of data " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Part 5. Data preprocessing" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Part 6. Feature engineering and description " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Part 7. Cross-validation, hyperparameter tuning" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Part 8. Validation and learning curves" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Part 9. Prediction for hold-out and test samples " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Part 10. Model evaluation with metrics description" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Part 11. Conclusions" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.6" } }, "nbformat": 4, "nbformat_minor": 2 }