These notebooks are widely used for coding in Python.
This is one of the most dominant languages for data science in the industry today because of its ease, flexibility, open-source nature. It has gained rapid popularity and acceptance in the ML community.
It is Numerical computing tool
It is data processing and data manipulation tool
It is data visualization tool.
It is easily the most widely used tool in the industry today. Google might have something to do with that!
This super flexible deep learning framework is giving major competition to TensorFlow. PyTorch has recently come into the limelight and was developed by researchers at Facebook
Simple and efficient tools for predictive data analysis. It features various Classification, Regression and clustering algorithms .
It is used for natural language processing
It is a platform for operating machine learning workloads in the cloud. Azure Machine Learning enables you to manage:
It is used extensively for building deep learning applications
Best-in-class content by leading faculty and industry leaders in the form of videos, cases and projectsDOWNLOAD SYLLABUS
Build a foundation for the most in-demand programming language of the 21st century.
Learn how to manipulate datasets in Python using Pandas which
is the most powerful library for data preparation and analysis.
Humans are visual learners and hence no task related to data is complete without visualisation. Learn to plot and interpret various graphs
in Python and observe how they make data analysis and drawing insights easier.
Learn how to find and analyze the patterns in the data to draw actionable insights.
a) Reading and Getting Data into R
b) Data Objects-Data Types & Data Structure.
c) Viewing Named Objects, Structure of Data Items, Manipulating and Processing Data in R (Creating, Accessing, Sorting data frames, Extracting, Combining, Merging, reshaping data frames)
d) Control Structures, Functions in R (numeric, character, statistical)
e) working with objects, Viewing Objects within Objects, Constructing Data Objects, Packages – Tidyverse, Dplyr, Tidyr etc., Queuing Theory,
f) Non parametric Tests- ANOVA, chi-Square, t-Test, U-Test
g) Interactive reporting with R markdown
Learners will fill in the shoes of an analyst at an investment bank and determine where the firm should invest. They will then have to explain their recommendations in lieu of the analysis conducted
Build a strong statistical foundation and learn how to ‘infer’ insights from a huge population using a small sample.
Understand how to formulate and validate hypotheses for a population to solve real-life business problems.
Venture into the machine learning community by learning how one variable can be predicted using several other variables through a housing dataset where you will predict the prices of houses based on various factors.
Learn your first binary classification technique by determining which customers of a telecom operator are likely to churn versus who are not to help the business retain customers.
Understand the basic building blocks of Naive Bayes and learn how to build an SMS Spam Ham Classifier using Naive Bayes technique.
Learn the pros and cons of simple and complex models and the different methods for quantifying model complexity, along with regularisation and cross validation.
Learn how to find a maximal marginal classifier using SVM, and use them to detect spam emails, recognize alphabets and more!
Learn how the human decision-making process can be replicated using a decision tree and other powerful ensemble algorithms.
Learn how weak learners can be ‘boosted’ with the help of each other and become strong learners using different boosting algorithms such as Adaboost, GBM, and XGBoost.
Learn how to group elements into different clusters when you don’t have any pre-defined labels to segregate them through K-means clustering, hierarchical clustering, and more.
Solve the most crucial business problem for a leading telecom operator in India and southeast Asia - predicting customer churn
Do you get annoyed by the constant spams in your mail box? Wouldn’t it be nice if we had a program to check your spellings? In this module learn how to build a spell checker & spam detector using techniques like phonetic hashing, bag-of-words, TF-IDF, etc.
Learn how to analyze the syntax or the grammatical structure of sentences with the help of algorithms & techniques like HMMs, Viterbi Algorithm, Named Entity Recognition (NER), etc.
Build a POS tagger for tagging unknown words using HMMs and modified Viterbi algorithm
Learn the most interesting area in the field of NLP and understand different techniques like word-embeddings, LSA, topic modeling to build an application that extracts opinions about socially relevant issues (such as demonetization) on social media platforms.
Imagine if you could make restaurant booking without opening Zomato. Build your own restaurant-search chatbot with the help of RASA - an open source framework and deploy it on Slack.
Learn the most sophisticated and cutting-edge technique in machine learning - Artificial Neural Networks or ANNs.
Build a neural network from scratch in Numpy to identify the type of skin cancer from images.
Learn the basics of CNN and OpenCV and apply it to Computer Vision tasks like detecting anomalies in chest X-Ray scans, vehicle detection to count and categorise them to help the government ascertain the width and strength of the road.
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Learning is very good here. Trainers are very good for Azure and Aws. Completed my Aws & Azure Training.
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Best institute offering a AWS & Azure course within this good cost. Trainer was always ready to clear our doubt and support us. Also they have a good student coordinator.
Enrolled here for the course of Linux, trainers are highly qualified with great experience, staffs were quite helpful Kavita and Alka.
Artifical Training content was very helpfull for me to get the job. Teaching and explanation was very good.Good experience overall.
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