Udemy course for free

Udemy Course For Free | Daily Free Courses Are Uploaded | Publisher :     Robert Fox - Jill Jenkins Course Language :   English Understanding Machine Learning as a Business Capability. Requirements No prior knowledge required. This course has no coding or complex mathematics. This class is the prerequisite for many other data science courses. Description This course has a simple mission: to give you a solid understanding of what Machine Learning is.   Mastering the terminology is your first step to understanding the ideas and capabilities.  Machine learning is a capability that business leaders should grasp if they want to extract value from data.   There's a lot of hype; but there's some truth: the use of modern data science techniques could translate to a leap forward in progress or a significant competitive advantage.  Often you can buy "AI-powered" solutions; but you should consider how your organization's core competencies could benefit from machine

  JOIN OUR TELEGRAM CHANNEL Requirements If students knows Python, that is well & good Anaconda Installation to work with the NumPy and Python Basic mathematics Willing to learn data analysis, data science or numerical computation for programm Description Hi, welcome to the 'NumPy For Data Science & Machine Learning' course. This forms the basis for everything else. The central object in Numpy is the Numpy array, on which you can do various operations. We know that the matrix and arrays play an important role in numerical computation and data analysis. Pandas and other ML or AI tools need tabular or array-like data to work efficiently, so using NumPy in Pandas and ML packages can reduce the time and improve the performance of the data computation. NumPy based arrays are 10 to 100 times (even more than 100 times) faster than the Python Lists, hence if you are planning to work as a Data Analyst or Data Scientist or Big Data Engine

Machine Learning - Regression and Classification (math Inc.) JOIN OUR TELEGRAM CHANNEL Description Machine learning is a branch of artificial intelligence (AI) focused on building applications that learn from data and improve their accuracy over time without being programmed to do so. In data science, an algorithm is a sequence of statistical processing steps. In machine learning, algorithms are 'trained' to find patterns and features in massive amounts of data in order to make decisions and predictions based on new data. The better the algorithm, the more accurate the decisions and predictions will become as it processes more data. Machine learning has led to some amazing results, like being able to analyze medical images and predict diseases on-par with human experts. Google's AlphaGo program was able to beat a world champion in the strategy game go using deep reinforcement learning. Machine learning is even being used to program self d