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  • Top 10 Machine Learning Algorithms for Beginners

    A beginner's introduction to the Top 10 Machine Learning (ML) algorithms, complete with figures and examples for easy understanding.

    Source: Kdnugget
    18555
  • 5 Reasons "Logistic Regression" should be the first thing you learn when becoming a Data Scientist

    I started my way in the Data Science world a few years back. I was a Software Engineer back then and I started to learn online first (before starting my Master's degree).

    Source: HOB
    12825
  • Understanding Decision Tree Algorithm with the help of Examples

    Decision Tree Algorithm is a part of supervised Machine Learning Algorithm. This algorithm is used for solving regression and classification problems just like other algorithms. This algorithm is basically used to predict the value from the passed trained data by applying learning decision rules. This is the most powerful algorithm among all as this algorithm can be easily visualized and understandable by the humans.

    Source: HOB
    17247
  • Machine Learning Can Reach Heights With These Algorithms

    Machine Learning Algorithms are those that can learn from data and improve from experience, without human intervention. Learning tasks may include learning the function that maps the input to the output, learning the hidden structure in unlabeled data where a class label is produced for a new instance by comparing the new instance (row) to instances from the training data, which were stored in memory.

    Source: HOB
    17796
  • Future Through The Eyes Of Data Science

    Once the Business Intelligence reports and dashboards have been prepared and insights which are extracted from them, this information becomes the basis for predicting future values. And the accuracy of these predictions lies in the methods used.

    Source: HOB
    23361
  • Get To Know Who is Actually A DATA SCIENTIST

    With only heavy statistical background professional have proper experience in this domain and recruiters should hire data scientists, who have a rich and strong background and capable to do their job. You can do data science without statistics, Data science without statistics is possible, even desirable. Data science is about automating these boring tasks. And automating much more advanced tasks.

    Source: HOB
    29202
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