Udemy - Kaggle Masterclass - build a Machine Learning Portfolio

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Kaggle Masterclass - build a Data Science Portfolio [TutsNode.com] - Kaggle Masterclass - build a Data Science Portfolio 8. Project House Price Prediction
  • 3. House Price Prediction using Random Forest.mp4 (121.3 MB)
  • 3. House Price Prediction using Random Forest.srt (23.6 KB)
  • 2. House Prices Dataset Description.srt (7.3 KB)
  • 1. Introduction to House Prices - Advanced Regression Techniques Competition.srt (4.1 KB)
  • 4. House Price Prediction using Random Forest Project Notebook.html (0.2 KB)
  • 2. House Prices Dataset Description.mp4 (40.1 MB)
  • 1. Introduction to House Prices - Advanced Regression Techniques Competition.mp4 (17.5 MB)
6. Project Titanic - Machine Learning from Disaster
  • 2. Implementing a Model to Predict Survival of Titanic Passengers.srt (18.5 KB)
  • 1. Introduction to the Titanic - Machine Learning from Disaster Competition.srt (12.2 KB)
  • 3. Titanic - Machine Learning from Disaster Project Notebook.html (0.2 KB)
  • 2. Implementing a Model to Predict Survival of Titanic Passengers.mp4 (68.0 MB)
  • 1. Introduction to the Titanic - Machine Learning from Disaster Competition.mp4 (50.7 MB)
10. Project Telco Customer Churn
  • 5. Survival Regression Analysis using Cox Proportional Hazard Regression Model.srt (13.6 KB)
  • 2. Telco Customer Churn Pipeline Data Analysis and Visualization.srt (10.2 KB)
  • 4. Survival Analysis to predict Churn using Kaplan-Meier Estimate.srt (9.3 KB)
  • 3. Telco Customer Churn Pipeline Data Preprocessing.srt (5.7 KB)
  • 1. Introduction to Telco Customer Churn Dataset.srt (3.9 KB)
  • 5. Survival Regression Analysis using Cox Proportional Hazard Regression Model.mp4 (78.1 MB)
  • 6. Survival Regression Analysis to Predict Churn Project Notebook.html (0.2 KB)
  • 2. Telco Customer Churn Pipeline Data Analysis and Visualization.mp4 (53.8 MB)
  • 4. Survival Analysis to predict Churn using Kaplan-Meier Estimate.mp4 (50.2 MB)
  • 3. Telco Customer Churn Pipeline Data Preprocessing.mp4 (32.8 MB)
  • 1. Introduction to Telco Customer Churn Dataset.mp4 (19.7 MB)
1. Kaggle Progression System
  • 2. Kaggle Medals.srt (2.3 KB)
  • 3. More on Kaggle Progression.srt (2.2 KB)
  • 1. Kaggle Categories and Performance Tiers.srt (5.7 KB)
  • 1. Kaggle Categories and Performance Tiers.mp4 (20.1 MB)
  • 2. Kaggle Medals.mp4 (9.0 MB)
  • 3. More on Kaggle Progression.mp4 (8.7 MB)
2. Kaggle Competitions
  • 1. Kaggle Competitions.srt (12.0 KB)
  • 2. Competition Formats.srt (5.3 KB)
  • 5. Making a Submission.srt (4.4 KB)
  • 3. Joining a Competition.srt (3.5 KB)
  • 4. Forming a Team.srt (3.2 KB)
  • 6. Data Leakage.srt (2.9 KB)
  • 1. Kaggle Competitions.mp4 (57.0 MB)
  • 2. Competition Formats.mp4 (24.4 MB)
  • 5. Making a Submission.mp4 (16.0 MB)
  • 3. Joining a Competition.mp4 (14.1 MB)
  • 4. Forming a Team.mp4 (11.3 MB)
  • 6. Data Leakage.mp4 (9.8 MB)
7. Project Iris Species Classification
  • 2. Coding an Iris Species Classifier in Sci-kit Learn.srt (10.8 KB)
  • 1. Introduction to the Iris Species Dataset.srt (1.6 KB)
  • 3. Iris Species Classifier Project Notebook.html (0.2 KB)
  • 2. Coding an Iris Species Classifier in Sci-kit Learn.mp4 (39.8 MB)
  • 1. Introduction to the Iris Species Dataset.mp4 (7.1 MB)
11. Project Avocado Prices Forecasting
  • 2. Avocado Price Forecasting using Facebook Prophet.srt (8.6 KB)
  • 1. Introduction to Avocado Prices Dataset.srt (1.2 KB)
  • 3. Avocado Price Forecasting using Facebook Prophet Project Notebook.html (0.2 KB)
  • 2. Avocado Price Forecasting using Facebook Prophet.mp4 (39.2 MB)
  • 1. Introduction to Avocado Prices Dataset.mp4 (6.5 MB)
9. Theory Survival Regression Analysis
  • 5. Survival Regression - Cox Proportional Hazard Regression Model.srt (7.8 KB)
  • 2. Censorship.srt (4.6 KB)
  • 4. Kaplan-Meier Estimate and Nelson Aalen Fitter.srt (3.5 KB)
  • 1. Introduction to Survival Analysis.srt (2.8 KB)
  • 3. The Survival Function and the Hazard Function.srt (2.8 KB)
  • 5. Survival Regression - Cox Proportional Hazard Regression Model.mp4 (52.2 MB)
  • 2. Censorship.mp4 (26.6 MB)
  • 4. Kaplan-Meier Estimate and Nelson Aalen Fitter.mp4 (22.0 MB)
  • 1. Introduction to Survival Analysis.mp4 (18.7 MB)
  • 3. The Survival Function and the Hazard Function.mp4 (18.3 MB)
3. Kaggle Datasets
  • 3. Creating a Dataset.srt (6.4 KB)
  • 1. Types of Datasets on Kaggle.srt (5.5 KB)
  • 2. Searching for Datasets.srt (4.1 KB)
  • 5. Kaggle Datasets - Technical Specifications.srt (1.4 KB)
  • 4. Organizations and Dataset Collaborations.srt (3.5 KB)
  • 1. Types of Datasets on Kaggle.mp4 (34.5 MB)
  • 3. Creating a Dataset.mp4 (32.7 MB)
  • 2. Searching for Datasets.mp4 (26.3 MB)
  • 4. Organizations and Dataset Collaborations.mp4 (25.0 MB)
  • 5. Kaggle Datasets - Technical Specifications.mp4 (11.6 MB)
4. Kaggle Kernels
  • 6. More on Kaggle Kernels.srt (5.2 KB)
  • 2. Searching for Kernels.srt (4.4 KB)
  • 1. Types of Kaggle Kernels.srt (3.8 KB)
  • 3. Kernel Editor.srt (2.3 KB)
  • 4. Data Sources.srt (1.2 KB)
  • 5. Collaborating on Kernels.srt (1.3 KB)
  • 7. Kaggle Kernels - Technical Specifications.srt (1.8 KB)
  • 2. Searching for Kernels.mp4 (22.1 MB)
  • 6. More on Kaggle Kernels.mp4 (21.5 MB)
  • 1. Types of Kaggle Kernels.mp4 (15.0 MB)
  • 3. Kernel Editor.mp4 (11.1 MB)
  • 7. Kaggle Kernels - Technical Specifications.mp4 (7.9 MB)
  • 4. Data Sources.mp4 (7.3 MB)
  • 5. Collaborating on Kernels.mp4 (6.6 MB)
5. Kaggle Public API
  • 15. Configurations.srt (2.7 KB)
  • 7. Creating and Maintaining Datasets.srt (2.6 KB)
  • 3. Listing Competitions and Competition Files.srt (2.6 KB)
  • 1. Installing and Authenticating.srt (1.8 KB)
  • 9. Listing Kaggle Kernels.srt (2.2 KB)
  • 2. Kaggle API with Competitions.srt (1.4 KB)
  • 6. Listi

Description


Description

This career-ready Masterclass is designed to help you gain hands-on and in-depth exposure to the domain of Data Science by adopting the learn by doing approach. And the best way to land your dream job is to build a portfolio of projects. And the best platform for a Data Scientist is Kaggle!

Over the years, Kaggle has become the most popular community for Data Scientists. Kaggle not only helps you learn new skills and apply new techniques, but it now plays a crucial role in your career as a Data Professional.

This course will give you in-depth hands-on experience with a variety of projects that include the necessary components to become a proficient data scientist. By completing the projects in this course, you will gain hands-on experience with these components and have a set of projects to reflect what you have learned. These components include the following:

Data Analysis and Wrangling using NumPy and Pandas.
Exploratory Data Analysis using Matplotlib and Seaborn.
Machine Learning using Scikit Learn.
Deep Learning using TensorFlow.
Time Series Forecasting using Facebook Prophet.
Time Series Forecasting using Scikit-Time.

This course primarily focuses on helping you stand out by building a portfolio comprising of a series of Jupyter Notebooks in Python that utilizes Competitions and Public Datasets hosted on the Kaggle platform. You will set up your Kaggle profile that will help you stand out for future employment opportunities.
Who this course is for:

Beginner Python Developers who want to get into Data Science.
Data Scientists looking forward to expand their skillset.
Data Scientists and Aspiring Data Scientists who wish to create a strong portfolio for potential career opportunities.

Requirements

Intermediate Python Programming Skills.

Last Updated 4/2021



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Udemy - Kaggle Masterclass - build a Machine Learning Portfolio

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1.4 GB
seeders:26
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Udemy - Kaggle Masterclass - build a Machine Learning Portfolio

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