Ankita Rafiz

In this blog, I am going to post my notes, assignments etc that I did during my course on ML Foundations by Great Learning. ML Maths Basics Topics Covered Line Concept Line, Planes and Hyper planes Vector Algebra-magnitude and dimension Vector Algebra-vector operations Dot Product Matrix Algebra Functions Maxima and Minima of Functions Chain Rule Maxima and Minima Applications in ML Gradient Descent using Partial Derivatives Intro to AI and ML AI-computer program that does something smart or makes smart decisions When computer program learns about the world from data we call it ML. We assume past is a good representation of future. Model building from data take data as input find patterns in data summarise the pattern in a mathematically precise way Machine Learning automates this model building. If data is without noise then finding a pattern is easy but unfortunately data contains both data and noise.  Noise is unstructured and random. It does not repeat itself. ML does not assume da

I am attending ML Series initiated by Women Who Code which is six week long program where each week some topics in ML are covered. I will be posting my notes and assignments for each week in this blog. ML Intro Series 1: Series 1 was divided into two parts ML basics and Hypothesis testing, also Introductory lab on how to use colab was provided. ML Basics/Intro What is Machine Learning? a subset of AI  class of computer algorithms that learns from data  algorithms that improve with experience data and outputs are provided that results in a function that maps input to output, which can be used in multiple scenarios Why ML now? large computing power big Data available technologies that deal with data available high storage capacity higher RAM available reduction in the gap between academia and industry Terms data features target variable Types of ML supervised unsupervised semi Supervised reinforcement Learning  Supervised Learning  known input and output, training examples unknown, funct

Hi, I have created a blog in which I will posting my progress on  Studying Association between Social Acceptance and Self Esteem with screenshots and blogs though Data Visualisation & Analysis. It is a course on Coursera consisting of Generating Research Question, Studying Frequency Distributions, Data Management Decisions & Data Visualisation. Check it at:  https://ankitarafiz.tumblr.com/ Do recommend changes and feedback for improvements!

Some Sample Screenshots from my Side Projects including OCDWebsite, Resume Builder, BMI Calculator, Screenshots of Posters, Some Case Studies on Jupyter Notebook, Maps using Folium, Rail website, Book Store, Dictionary, Motion_Detector, Data Management & Visualization                   I will be uploading my screenshot samples & my learning in form of tutorials & blogs from projects and case studies. Do let me know for improvements and feedback! Github Profile:  https://github.com/Ankita002 Kaggle Profile:  https://www.kaggle.com/ankitarafiz