Udemy - Kaggle Masterclass - build a Machine Learning Portfolio

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Udemy - Kaggle Masterclass - build a Machine Learning Portfolio (Size: 1.4 GB)
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  1 352 KB
  1. Installing and Authenticating.mp4 15.4 MB
  1. Installing and Authenticating.srt 1.8 KB
  1. Introduction to Avocado Prices Dataset.mp4 6.5 MB
  1. Introduction to Avocado Prices Dataset.srt 1.2 KB
  1. Introduction to House Prices - Advanced Regression Techniques Competition.mp4 17.5 MB
  1. Introduction to House Prices - Advanced Regression Techniques Competition.srt 4.1 KB
  1. Introduction to Survival Analysis.mp4 18.7 MB
  1. Introduction to Survival Analysis.srt 2.8 KB
  1. Introduction to Telco Customer Churn Dataset.mp4 19.7 MB
  1. Introduction to Telco Customer Churn Dataset.srt 3.9 KB
  1. Introduction to the Iris Species Dataset.mp4 7.1 MB
  1. Introduction to the Iris Species Dataset.srt 1.6 KB
  1. Introduction to the Titanic - Machine Learning from Disaster Competition.mp4 50.7 MB
  1. Introduction to the Titanic - Machine Learning from Disaster Competition.srt 12.2 KB
  1. Kaggle Categories and Performance Tiers.mp4 20.1 MB
  1. Kaggle Categories and Performance Tiers.srt 5.7 KB
  1. Kaggle Competitions.mp4 57 MB
  1. Kaggle Competitions.srt 12 KB
  1. New York City Taxi Trip Duration Prediction and Anomaly Detection Notebook.html 204.8 B
  1. Types of Datasets on Kaggle.mp4 34.5 MB
  1. Types of Datasets on Kaggle.srt 5.5 KB
  1. Types of Kaggle Kernels.mp4 15 MB
  1. Types of Kaggle Kernels.srt 3.8 KB
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  10. Kernel Metadata File.mp4 8.8 MB
  10. Kernel Metadata File.srt 1.1 KB
  11. Push and Pull a Kernel.mp4 8.6 MB
  11. Push and Pull a Kernel.srt 1.1 KB
  12. Checking the Status and Output of a Kernel.mp4 10.2 MB
  12. Checking the Status and Output of a Kernel.srt 1.2 KB
  13. Creating and Running a New Kernel.mp4 14.2 MB
  13. Creating and Running a New Kernel.srt 1.4 KB
  14. Creating and Running a New Kernel Version.mp4 17.8 MB
  14. Creating and Running a New Kernel Version.srt 1.2 KB
  15. Configurations.mp4 18.3 MB
  15. Configurations.srt 2.7 KB
  2. Avocado Price Forecasting using Facebook Prophet.mp4 39.2 MB
  2. Avocado Price Forecasting using Facebook Prophet.srt 8.6 KB
  2. Censorship.mp4 26.6 MB
  2. Censorship.srt 4.6 KB
  2. Coding an Iris Species Classifier in Sci-kit Learn.mp4 39.8 MB
  2. Coding an Iris Species Classifier in Sci-kit Learn.srt 10.8 KB
  2. Competition Formats.mp4 24.4 MB
  2. Competition Formats.srt 5.3 KB
  2. House Prices Dataset Description.mp4 40.1 MB
  2. House Prices Dataset Description.srt 7.3 KB
  2. Implementing a Model to Predict Survival of Titanic Passengers.mp4 68 MB
  2. Implementing a Model to Predict Survival of Titanic Passengers.srt 18.5 KB
  2. Kaggle API with Competitions.mp4 11.4 MB
  2. Kaggle API with Competitions.srt 1.4 KB
  2. Kaggle Medals.mp4 9 MB
  2. Kaggle Medals.srt 2.3 KB
  2. Searching for Datasets.mp4 26.3 MB
  2. Searching for Datasets.srt 4.1 KB
  2. Searching for Kernels.mp4 22.1 MB
  2. Searching for Kernels.srt 4.4 KB
  2. Telco Customer Churn Pipeline Data Analysis and Visualization.mp4 53.8 MB
  2. Telco Customer Churn Pipeline Data Analysis and Visualization.srt 10.2 KB
  3. Avocado Price Forecasting using Facebook Prophet Project Notebook.html 204.8 B
  3. Creating a Dataset.mp4 32.7 MB
  3. Creating a Dataset.srt 6.4 KB
  3. House Price Prediction using Random Forest.mp4 121.3 MB
  3. House Price Prediction using Random Forest.srt 23.6 KB
  3. Iris Species Classifier Project Notebook.html 204.8 B
  3. Joining a Competition.mp4 14.1 MB
  3. Joining a Competition.srt 3.5 KB
  3. Kernel Editor.mp4 11.1 MB
  3. Kernel Editor.srt 2.3 KB
  3. Listing Competitions and Competition Files.mp4 19.5 MB
  3. Listing Competitions and Competition Files.srt 2.6 KB
  3. More on Kaggle Progression.mp4 8.7 MB
  3. More on Kaggle Progression.srt 2.2 KB
  3. Telco Customer Churn Pipeline Data Preprocessing.mp4 32.8 MB
  3. Telco Customer Churn Pipeline Data Preprocessing.srt 5.7 KB
  3. The Survival Function and the Hazard Function.mp4 18.3 MB
  3. The Survival Function and the Hazard Function.srt 2.8 KB
  3. Titanic - Machine Learning from Disaster Project Notebook.html 204.8 B
  4. Data Sources.mp4 7.3 MB
  4. Data Sources.srt 1.2 KB
  4. Downloading a Competition.mp4 11.4 MB
  4. Downloading a Competition.srt 1.5 KB
  4. Forming a Team.mp4 11.3 MB
  4. Forming a Team.srt 3.2 KB
  4. House Price Prediction using Random Forest Project Notebook.html 204.8 B
  4. Kaplan-Meier Estimate and Nelson Aalen Fitter.srt 3.5 KB
  4. Organizations and Dataset Collaborations.mp4 25 MB
  4 250.8 KB
  4. Kaplan-Meier Estimate and Nelson Aalen Fitter.mp4 22 MB
  4. Organizations and Dataset Collaborations.srt 3.5 KB
  4. Survival Analysis to predict Churn using Kaplan-Meier Estimate.mp4 50.2 MB
  4. Survival Analysis to predict Churn using Kaplan-Meier Estimate.srt 9.3 KB
  5. Collaborating on Kernels.mp4 6.6 MB
  5. Collaborating on Kernels.srt 1.3 KB
  5. Kaggle API with Datasets.mp4 12.1 MB
  5. Kaggle API with Datasets.srt 1 KB
  5. Kaggle Datasets - Technical Specifications.mp4 11.6 MB
  5. Kaggle Datasets - Technical Specifications.srt 1.4 KB
  5. Making a Submission.mp4 16 MB
  5. Making a Submission.srt 4.4 KB
  5. Survival Regression - Cox Proportional Hazard Regression Model.mp4 52.2 MB
  5. Survival Regression - Cox Proportional Hazard Regression Model.srt 7.8 KB
  5. Survival Regression Analysis using Cox Proportional Hazard Regression Model.mp4 78.1 MB
  5. Survival Regression Analysis using Cox Proportional Hazard Regression Model.srt 13.6 KB
  5 267.7 KB
  6. Data Leakage.mp4 9.8 MB
  6. Data Leakage.srt 2.9 KB
  6. Listing and Downloading Datasets.mp4 16.3 MB
  6. Listing and Downloading Datasets.srt 2 KB
  6. More on Kaggle Kernels.mp4 21.5 MB
  6. More on Kaggle Kernels.srt 5.2 KB
  6. Survival Regression Analysis to Predict Churn Project Notebook.html 204.8 B
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  7. Creating and Maintaining Datasets.mp4 23 MB
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  7. Creating and Maintaining Datasets.srt 2.6 KB
  7. Kaggle Kernels - Technical Specifications.mp4 7.9 MB
  7. Kaggle Kernels - Technical Specifications.srt 1.8 KB
  8. Kaggle API with Kernels.mp4 14 MB
  8. Kaggle API with Kernels.srt 1.3 KB
  9. Listing Kaggle Kernels.mp4 17.4 MB
  9. Listing Kaggle Kernels.srt 2.2 KB
  TutsNode.com.txt 102.4 B
  [TGx]Downloaded from torrentgalaxy.to .txt 614.4 B
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  ▲ 172 total files

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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