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Machine Learning Classification Bootcamp In Python

Construct 10 Sensible Initiatives and Advance Your Expertise in Machine Learning Utilizing Python and Scikit Study

What you’ll study

  • Apply superior machine studying fashions to carry out sentiment evaluation and classify buyer opinions equivalent to Amazon Alexa merchandise opinions
  • Perceive the speculation and instinct behind a number of machine studying algorithms equivalent to Okay-Nearest Neighbors, Assist Vector Machines (SVM), Determination Timber, Random Forest, Naive Bayes, and Logistic Regression
  • Implement classification algorithms in Scikit-Study for Okay-Nearest Neighbors, Assist Vector Machines (SVM), Determination Timber, Random Forest, Naive Bayes, and Logistic Regression
  • Construct an e-mail spam classifier utilizing Naive Bayes classification Approach
  • Apply machine studying fashions to Healthcare functions equivalent to Most cancers and Kyphosis illnesses classification
  • Develop Fashions to foretell buyer habits in direction of focused Fb Adverts
  • Classify information utilizing Okay-Nearest Neighbors, Assist Vector Machines (SVM), Determination Timber, Random Forest, Naive Bayes, and Logistic Regression
  • Construct an in-retailer characteristic to foretell buyer’s size utilizing their options
  • Develop a fraud detection classifier utilizing Machine Learning Strategies
  • Grasp Python Seaborn library for statistical plots
  • Perceive the distinction between Machine Learning, Deep Learning and Synthetic Intelligence
  • Carry out characteristic engineering and clear your coaching and testing information to take away outliers
  • Grasp Python and Scikit-Study for Knowledge Science and Machine Learning
  • Study to make use of Python Matplotlib library for information Plotting

Necessities

  • Primary data of Python Programming
  • Skilled pc person

Description

Are you able to grasp Machine Learning methods and Kick-off your profession as a Knowledge Scientist?!

You got here to the precise place!

Machine Learning ability is among the high expertise to accumulate in 2019 with a median wage of over $114,000 in the USA based on PayScale! The overall variety of ML jobs over the previous two years has grown round 600 p.c and anticipated to develop much more by 2020.

This course supplies college students with data, fingers-on expertise of state-of-the-artwork machine studying classification methods equivalent to

  • Logistic Regression
  • Determination Timber
  • Random Forest
  • Naïve Bayes
  • Assist Vector Machines (SVM)

In this course, we’re going to present college students with data of key points of state-of-the-artwork classification methods. We’re going to construct 10 initiatives from scratch utilizing actual world dataset, right here’s a pattern of the initiatives we will likely be engaged on:

  • Construct an e-mail spam classifier.
  • Carry out sentiment evaluation and analyze buyer opinions for Amazon Alexa merchandise.
  • Predict the survival charges of the titanic primarily based on the passenger options.
  • Predict buyer habits in direction of focused advertising advertisements on Fb.
  • Predicting financial institution shopper’s eligibility to retire given their options equivalent to age and 401K financial savings.
  • Predict most cancers and Kyphosis illnesses.
  • Detect fraud in bank card transactions.

Key Course Highlights:

  • This complete machine studying course contains over 75 HD video lectures with over 11 hours of video content material.
  • The course incorporates 10 sensible fingers-on python coding initiatives that college students can add to their portfolio of initiatives.
  • No intimidating arithmetic, we’ll cowl the speculation and instinct in clear, easy and simple approach.
  • All Jupyter noteboooks (codes) and slides are supplied.
  • 10+ years of expertise in machine studying and deep studying in each tutorial and industrial settings have been compiled on this course.

College students who enroll on this course will grasp machine studying classification fashions and might instantly apply these expertise to unravel actual world difficult issues.

Who this course is for:

  • Knowledge Science Fans wanting to boost their machine studying expertise
  • Python programmers interested in Machine Learning and Knowledge Science
  • Programmers or builders who need to make a shift into the profitable information science and machine studying profession path
  • Technologists wanting to achieve an understanding of how machine studying fashions work
  • Knowledge analysts who need to transition into the Tech business

Created by Dr. Ryan Ahmed, Ph.D., MBA, Mitchell Bouchard, Ligency Workforce
Final up to date 2/2021
English
English [Auto]

Dimension: 5.72 GB

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