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Machine learning: A data-driven approach for success

HomeEventsWebinarsMachine learning: A data-driven approach for success
feature
Date
date 6th Dec, 2019
Time
time 9:00 AM - 10:30 AM EDT
Mode
mode Online

“Machine learning will automate jobs that most people thought could only be done by people”

  • Dave Waters

Machine learning today has gained immense popularity, and is gradually impacting every aspect of our lives. It has become quite the trend in the fourth industrial revolution and is definitely here to stay. As a part of the broad category of data science, machine learning takes data science a step further by using algorithms that are greatly helpful for organizations and individuals in making informed decisions. It helps us study, process and analyze data better, by incorporating machines into the routine, thereby reducing the time to get the results, and eliminating the scope of errors.

“A baby learns to crawl, walk and then run. We are in the crawling stage, when it comes to applying machine learning.

Machine learning is a highly sought after career option in the market currently. Companies big and small, everywhere on the globe, are looking for trained and skilled machine learning professionals, who are a master of their craft and can help organizations achieve their goals.

Machine learning and the Python programming language are not new in any way, but have gained a lot of fresh momentum in the past few years. So take this leap with us and gain the skills to achieve success with a data-driven approach using machine learning. Cognixia is hosting a live webinar on “Machine learning: A data-driven approach for success” on 6 December 2019 from 7:30 p.m. to 9:30 p.m. IST.

This webinar broadly covers:

  • Why use Python for machine learning?
  • Basic syntax
  • Learning Python programming
  • NumPy, Pandas, Matplotlib
  • Data wrangling
  • Exploratory Data Analysis (EDA)
  • Basics of machine learning
  • Supervised learning – linear regression
  • Unsupervised learning – Logistic regression, decision tree, random forest, SVM, Naive Bayes k-means clustering
  • Reinforcement leaning – Q-learning
  • Dimensionality reduction – PCA/LDA
  • Market basket analysis – association rules and Apriori algorithm
  • Time series analysis – ARIMA model
  • Introduction to artificial intelligence
  • ANN and Deep learning
  • TensorFlow

Every participant who attends the complete webinar will get a Certificate of Participation from Cognixia.

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