[95% Off Super Offer] 2019 Machine Learning Classification Bootcamp in Python

Bootcamp
Build 10 Practical Projects and Advance Your Skills in Machine Learning Using Python and Scikit Learn

What you’ll learn
  1. Apply advanced machine learning models to perform sentiment analysis and classify customer reviews such as Amazon Alexa products reviews
  2. Understand the theory and intuition behind several machine learning algorithms such as K-Nearest Neighbors, Support Vector Machines (SVM), Decision Trees, Random Forest, Naive Bayes, and Logistic Regression

  3. Implement classification algorithms in Scikit-Learn for K-Nearest Neighbors, Support Vector Machines (SVM), Decision Trees, Random Forest, Naive Bayes, and Logistic Regression

  4. Build an e-mail spam classifier using Naive Bayes classification Technique
  5. Apply machine learning models to Healthcare applications such as Cancer and Kyphosis diseases classification
  6. Develop Models to predict customer behavior towards targeted Facebook Ads
  7. Classify data using K-Nearest Neighbors, Support Vector Machines (SVM), Decision Trees, Random Forest, Naive Bayes, and Logistic Regression
  8. Build an in-store feature to predict customer’s size using their features
  9. Develop a fraud detection classifier using Machine Learning Techniques
  10. Master Python Seaborn library for statistical plots
  11. Understand the difference between Machine Learning, Deep Learning and Artificial Intelligence
  12. Perform feature engineering and clean your training and testing data to remove outliers
  13. Master Python and Scikit-Learn for Data Science and Machine Learning
  14. Learn to use Python Matplotlib library for data Plotting
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Who this course is for:
  • Data Science Enthusiasts wanting to enhance their machine learning skills
  • Python programmers curious about Machine Learning and Data Science
  • Programmers or developers who want to make a shift into the lucrative data science and machine learning career path
  • Technologists wanting to gain an understanding of how machine learning models work
  • Data analysts who want to transition into the Tech industry
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