Machine Learning Workshops

Machine Learning BootCamp

( Five Days )


( For Upcoming Schedule and Fees Refer below )

About Machine Learning

Machine learning is a field of computer science that often uses statistical techniques to give computers the ability to "learn" (i.e., progressively improve performance on a specific task) with data, without being explicitly programmed.
Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves. The process of learning begins with observations or data, such as examples, direct experience, or instruction, in order to look for patterns in data and make better decisions in the future based on the examples that we provide. The primary aim is to allow the computers learn automatically without human intervention or assistance and adjust actions accordingly.



About the workshop

This is a five day workshop which will progressively take you through various Supervised Learning algorithms, providing hands on experience on problems based on Classification, Regression, Textual analysis, Time Series analysis, Feature Engineering and Optimization. At the end of this workshop, you would have solved and uploaded your results to the respective sites.



Introduction to Machine Learning

This session gives introduction for what machine learning is and where can machine learning be applied.This also provides an overview of various types of machine learning.This also provides a path on where to start for establishing a career in machine learning and the process that has to be followed to make predictions on a machine learning problem.


Python For Machine Learning

This session gives introduction for what machine learning is and where can machine learning be applied.This also provides hands on experience on python packages like numpy, pandas, matplotlib and seaborn necessary for data analysis and machine learning using python.





Logistic Regression - Kaggle Titanic

Logistic Regression is a statistical method for analyzing a dataset in which there are one or more independent variables that determine an outcome. The outcome is measured with a dichotomous variable (in which there are only two possible outcomes). You would be able to use Logistic Regression algorithms to determine if passengers on Titanic survived or died based on their attributes.



Linear Regression, Random Forest Regression - Predict Annual Returns



Linear Regression is a standard Statistical Data Analysis technique which is used to determine the extent to which there is a linear relationship between a dependent variable and one or more independent variables. Random Forests are an ensemble learning method for classification and regression. Through this workshop, you will get to know how random forests can be used for regression. You will get to solve a problem which is asked in HackerEarth's Brain Waves Competition using the above two algorithms.



Classification and Feature Engineering using XGBoost - Predict the Criminals

XGBoost Algorithm has become the ultimate weapon of many data scientists. It’s a highly sophisticated algorithm, powerful enough to deal with all sorts of irregularities of data and is capable to perform parallel computation. It has both linear model solver and tree learning algorithms. Participants will get to know about XGBoost, Feature Engineering Using XGBoost and Optimization of hyperparameters using XGBoost through hands on experience.



NLTK with Naive Bayes Classifier - Twitter Sentiment Analysis

Most of the data in today’s world is being generated as we speak, as we tweet, as we send messages on social media and in various other activities. Working on this data has become necessary to derive useful patterns which will help in serving the customers better and also helps in business growth. Despite having this raw data it cannot be used without performing necessary processing. Participants will be provided hands on experience on natural language processing tools along with end to end walk-through on how to classify the twitter comments using the NLTK Tools.



Time Series Analysis - Stock Market Prediction

We predict the future using the observations from the present and give equal weightage to all the observations. It is necessary to give importance to certain observations over another when dealing with time dependent data and also when there are seasonal trends in the data. So this workshop will focus on coverage of all techniques necessary to handle Time Series Data.

Key takeaways



Recognizing the problem

A high level overview of what machine learning is and to recognize the problems that can be solved with Machine Learning.

Selecting the techniques

Select the right technique to solve the problem (is it a classification problem? a regression? needs preprocessing?).

Tools

A few libraries like Numpy, Pandas, Scikit-Learn, to start your learning experience, that you can improve upon.

Certificate

A certificate for succesful completion of the course.

Conclusion

Finally, you would be able to decide if Machine Learning is for you and what you would have to do next, if you want to make this your career.



Prerequisites



  • Having a good knowledge of programming concepts (writing loops, data structures, functions and recursive functions).
  • Knowledge of Python. (If you are not sure about your knowledge of python, sign up for the Basic Python for Data Science course).
  • Laptop with Wifi capability and Python 3.x installed.
  • A desire and thirst for knowledge.


Upcoming Schedule



Location City Workshop Details Timings Fees Register
Hinjowadi Pune Machine Learning Bootcamp July 17th, 2018 to July 21st, 2018 Rs.8000 to
Rs.12,000

Chief Facilitator


Avatar

Venkatesh Tadinada

Venkatesh Tadinada is passionate about data. "In God we trust, all others bring data," said Edward Deming, a philosophy wholly imbibed by Venkat. For the last 25 years, he has been working in various domains and various technologies with DATA as a common theme. Starting with Data Warehouses, proceeding on to Data Mining, Business Intelligence and now Machine Learning, Deep Learning & AI.

He successfully co-founded and exited a couple of startups so far. One of which is of Business Intelligence for Enterprises and the other is an Insurance sector product. Currently, he is invested in a few startups in the ML area and also sits on the boards of a few more.

Venkatesh has a Masters in Computers Science and an MBA. He brings his formal education and experience, combined with his passion for DATA to develop Predictive Analytics capabilities to his enterprise clients in pharmaceutical and insurance verticals.

Venkatesh in his spare time also follows his passion for teaching by conducting workshops in Machine Learning where he coaches aspiring students in the joy of DATA.



Machine Learning Workshops