Core Machine Learning

Learn Machine Learning topics in-depth, which covers both the aspects practically, and mathematically

Note: DON'T BUY ANY COURSE FROM HERE, IT'S NOT AN UPDATED BATCH, If you've already bought, please email team@antern.co

Instructor: Ayush SinghLanguage: English

Overview of the Course

Note: DON'T BUY ANY COURSE FROM HERE, IT'S NOT AN UPDATED BATCH, If you've already bought, please email team@antern.co

In this course, you will get to learn machine learning topics in-depth, it covers both the aspects practically & mathematically. You will learn in-depth mathematics behind algorithms and you will implement these algorithms, and techniques from scratch as well.

We start by covering mathematics review parts that are required for successfully completing this course such as calculus, linear algebra, and probability theory. We are not only covering a wide range of theorey, but we are also covering various case studies, machine learning system designs, good resume-level projects taken from Kaggle competitions that solve real-world problems, large-scale machine learning, and a lot more.

WHAT DO YOU GET?

Name: Core Machine Learning
Brand: Ayush Singh
SKU: 633ea7dbe4b02d25db3f202d
Price: 3000 INR
Availability: InStock

You will create data pipeline workflows to
analyze, visualize, and gain insights from data.

Understand Machine Learning from top to bottom.

You will build a portfolio of projects with real-world data.

Master critical Machine Learning skills.

Create supervised machine learning
algorithms to predict classes.

Understand the complete production
workflow for the machine learning lifecycle.

Explore how to deploy your machine-learning
models as interactive APIs.

WE ARE ANTERN

LEARN WITH
HAND MADE NOTES

GET YOUR NOTES NOW >>

THE SYLLABUS

01.

Prerequisites

Linear Algebra
Calculus
Statistics & Probability

02.

Core Data

Pandas
Numpy
Matplotlib
Project on Data Analysis & Data Visualisation

03.

Supervised ML & ML Techniques

Introduction to Machine Learning
Supervised Learning - Linear Regression & Regression Analysis.
Supervised Learning - Logistic Regression
Supervised Learning - Generalised Learning Model
Regularisation
Supervised Learning - Naive Bayes
Supervised Learning - Support Vector Machine
Learning Theory - Bias & Variance Trade-off, & other Trade-offs
Feature Engineering Techniques
Decision Trees and Ensemble Learning
Feature Selection Techniques

04.

Unsupervised Learning

Unsupervised Learning - K-means clustering
Unsupervised Learning - K-Nearest Neighbour
Unsupervised Learning - Hierarchal clustering
Unsupervised Learning - PCA & ICA
Reviewing Latest Techniques for working on data & applying algorithms

05.

Miscellaneous Topics in Machine Learning

MLOps - Product scoping, pipelines, tools, experiment tracking,
CI/CD pipeline, data versioning, packaging and etc.
Machine Learning System Design Case studies
( 10+ company case studies )
Machine Learning Interview Preparation
Guest lecturing by Top Pioneers in Machine Learning

KEY FEATURES

REAL-WORLD ALGORITHMS

Students will master machine learning techniques and apply these algorithms in the real world with careful consideration of data.
.

FIXING A REAL PROBLEM

Students will learn to apply machine learning to a real-world problem, by following the full machine learning pipeline like data ingestion, processing and etc.

DESIGN YOUR OWN ML SYSTEM

Students will be able to design their own machine-learning systems in the real world, they will be able to think about problems from various points of view.

WRITE A RESEARCH PAPER

Students will work on writing their own research papers guided by competent professionals in the industry.

LEARN TO FIX ALGORITHMS

They will not only learn algorithms, but they will also learn to fix the algorithm if the algorithm is not performing well on the data.

GET A STATISTICIAN'S MINDSET

Throughout the course with the type of practice we provide, they will adopt a Statistician's mindset.

WORK ON KAGGLE PROJECTS

Students will be able to do Kaggle competitions and actively work on complicated machine learning projects confidently whether it be alone or in a team.

MASTER THE ML INTERVIEW

Students will be confident in sitting for an interview for Machine Learning Engineering Or Data Scientist Role.

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