schedule Aug 30th 10:00 AM - 06:00 PM place Mars people 28 Interested

By now it is evident that a solid math foundation is indispensable if one has to get into Data science in an honest-to-goodness way. Unfortunately, for many of us math was just a means to get better scores at school-level and never really a means to understand the world around us.
That systemic failure (education system) causes many of us to feel a “gap” when learning data science concepts. It is high time that we acknowledge that gap and take remedial action.

The purpose of the workshop is to develop an intuitive understanding of the concepts.
We let go the fear of rigorous notation and embrace the rationale behind it.
The intended key take away for participants is confidence to deal with math.

 
4 favorite thumb_down thumb_up 0 comments visibility_off  Remove from Watchlist visibility  Add to Watchlist
 

Outline/structure of the Session

  • Warm up exercises (Indices and Logarithms)
  • Functions as transformations
  • Composing functions to make complex functions (not functions of complex variables)
  • Calculus concepts
    • Derivative
      • concept
      • formal definition
      • derivatives of complex (composed) functions
    • Integration
      • concept
  • Linear Algebra concepts
    • Vector
    • Matrix as transformation
    • Conceptual understanding of Determinant
    • Inverse of a matrix
    • Conceptual understanding of Eigen Values & Eigen Vectors

Learning Outcome

The participants will walk out feeling confident about fundamental mathematical concepts.
Mathematics would no longer be an hindrance in their learning path.

Target Audience

Target audience: 1. developers who feel rusty with math and want to learn it anew 2. Managers / testers who need to understand what their team members are talking about. 3. Anyone who wishes to get into data science projects but sees math as the obstacle.

Prerequisite

While you won’t need any particular software for this workshop, you will need the following:

  1. Willingness to think !!
  2. a notepad and a pen
  3. courage to walk up to the board to show your awesome solutions to every one else !
  4. a device with a browser and internet .. preferably bigger screens, but mobiles can do as well.
schedule Submitted 5 months ago

Comments Subscribe to Comments

comment Comment on this Submission

  • Liked Favio Vázquez
    keyboard_arrow_down

    Favio Vázquez - Agile Data Science Workflows with Python, Spark and Optimus

    Favio Vázquez
    Favio Vázquez
    Sr. Data Scientist
    Raken Data Group
    schedule 4 months ago
    Sold Out!
    480 Mins
    Workshop
    Intermediate

    Cleaning, Preparing , Transforming and Exploring Data is the most time-consuming and least enjoyable data science task, but one of the most important ones. With Optimus we’ve solve this problem for small or huge datasets, also improving a whole workflow for data science, making it easier for everyone. You will learn how the combination of Apache Spark and Optimus with the Python ecosystem can form a whole framework for Agile Data Science allowing people and companies to go further, and beyond their common sense and intuition to solve complex business problems.

  • Liked Saurabh Deshpande
    keyboard_arrow_down

    Saurabh Deshpande - Introduction to reinforcement learning using Python and OpenAI Gym

    Saurabh Deshpande
    Saurabh Deshpande
    Sr. Technical Consultant
    SAS
    schedule 5 months ago
    Sold Out!
    90 Mins
    Workshop
    Advanced

    Reinforcement Learning algorithms becoming more and more sophisticated every day which is evident from the recent win of AlphaGo and AlphaGo Zero (https://deepmind.com/blog/alphago-zero-learning-scratch/ ). OpenAI has provided toolkit openai gym for research and development of Reinforcement Learning algorithms.

    In this workshop, we will focus on introduction to the basic concepts and algorithms in Reinforcement Learning and hands on coding.

    Content

    • Introduction to Reinforcement Learning Concepts and teminologies
    • Setting up OpenAI Gym and other dependencies
    • Introducing OpenAI Gym and its APIs
    • Implementing simple algorithms using couple of OpenAI Gym Environments
    • Demo of Deep Reinforcement Learning using one of the OpenAI Gym Atari game

  • Abhijith
    Abhijith
    Data Scientist
    Julia Computing
    schedule 5 months ago
    Sold Out!
    480 Mins
    Workshop
    Intermediate

    You have been hearing about machine learning (ML) and artificial intelligence (AI) everywhere. You have heard about computers recognizing images, generating speech, natural language, and beating humans at Chess and Go.

    The objectives of the workshop:

    1. Learn machine learning, deep learning and AI concepts

    2. Provide hands-on training so that students can write applications in AI

    3. Provide ability to run real machine learning production examples

    4. Understand programming techniques that underlie the production software

    The concepts will be taught in Julia, a modern language for numerical computing and machine learning - but they can be applied in any language the audience are familiar with.

    Workshop will be structured as “reverse classroom” based laboratory exercises that have proven to be engaging and effective learning devices. Knowledgeable facilitators will help students learn the material and extrapolate to custom real world situations.

  • Liked Sai Charan J
    keyboard_arrow_down

    Sai Charan J - Self Learning - Data Science

    Sai Charan J
    Sai Charan J
    Data Scientist
    MTW Labs
    schedule 5 months ago
    Sold Out!
    45 Mins
    Workshop
    Beginner

    For people from a non-technical background, I recommend formal academic programs. And then raising the bar comes data-driven scientist - Self Taught Data Scientist! These people are trendsetters, go way deep & play with data. They love data crunching & are seen solving real-time problems!

    If that's you, then let's wave our hands!

  • Liked Harshad Saykhedkar
    keyboard_arrow_down

    Harshad Saykhedkar - Linear Algebra for Machine Learning Workshop

    240 Mins
    Workshop
    Beginner

    Linear Algebra, Optimization & Statistics is base of all machine learning. This workshop will cover required linear algebra for machine learning in a hands on way through short code examples. We will cover basic theory, interesting applications and the big picture.

  • Liked Saurabh Deshpande
    keyboard_arrow_down

    Saurabh Deshpande - Introduction to Natural Language Processing using Python

    Saurabh Deshpande
    Saurabh Deshpande
    Sr. Technical Consultant
    SAS
    schedule 5 months ago
    Sold Out!
    90 Mins
    Workshop
    Intermediate

    Python ecosystem for Natural language processing has evolved in last decade and rich set of open source tools and data sets are now available.

    In this session, we will go over basics of Natural language processing along with sample code demonstration and hands on tutorials using following famous python libraries,

    1. NLTK : One of the oldest and famous library for natural language analysis for researchers
    2. Stanford CoreNLP : Production ready NLP library. (Written in java but has many open source python wrappers)
    3. SpaCy: Comparatively new python NLP toolkit marketed as 'Industrial Strength' python library.

    Session will introduce the various use cases and basic concepts related to the natural language processing with demo and hands on tutorials

    Following NLP fundamentals will be discussed,

    - Syntax Vs. Semantics

    - Regular Expressions (Demo and Hands on)

    - Word Embeddings (Demo and Hands on)

    - Word Tokenization (Demo and Hands on)

    - Part of Speech Tagging (Demo and Hands on)

    - Text Similarity (Demo and Hands on)

    - Text Summarization

    - Named Entity Recognition ((Demo and Hands on))

    - Sentiment Analysis (Demo and Hands on)

  • Liked Venkatraman J
    keyboard_arrow_down

    Venkatraman J - Hands on Data Science. Get hands dirty with real code!!!

    Venkatraman J
    Venkatraman J
    Sr. Software engineer
    Metapack
    schedule 5 months ago
    Sold Out!
    45 Mins
    Workshop
    Intermediate

    Data science refers to the science of extracting useful information from data. Knowledge discovery in data bases, data mining, Information extraction also closely match with data science. Supervised learning,Semi supervised learning,Un supervised learning methodologies are out of Academia and penetrated deep into the industry leading to actionable insights, dashboard driven development, data driven reasoning and so on. Data science has been the buzzword for last few years in industry with only a handful of data scientists around the world. The industry needs more and more data scientists in future to solve problems using statistical techniques. The exponential availability of unstructured data from the web has thrown huge challenges to data scientists to exploit them before driving conclusions.

    Now that's overload of information and buzzwords. It all has to start somewhere? Where and how to start? How to get hands dirty rather than just reading books and blogs. Is it really science or just code?. Let's get into code to talk data science.

    In this workshop i will show the tools required to do real data science rather than just reading by building real models using Deep neural networks and show live demo of the same. Also share some of the key data science techniques every aspiring data scientist should have to thrive in the industry.