About the Machine Learning Course
Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence. A lot of opportunities are out there in the field of ml and AI in India. People already using machine learning in fields of image processing, pattern analysis, marketing, data analysis have a pretty good future in India. The Machine Learning workshop provides the participants technical training on the concepts and Machine Learning algorithms to develop the code. Participants will also learn to use different Python libraries. Instruction cum aided with live projects which will allow students to grasp concepts of the complete machine learning development lifecycle.
LEARNING PATH
Day 1 Python Programming – Fundamentals
Day 2 Python – Tools  Syntaxes & Data Structures
Day 3 Machine Learning Course Concepts
Day 4 Pandas Library – Introduction
Day 5 Pandas – Data Structures
Day 6 Numpy library – Array Operations  Mathematical Functions
Day 7 Numpy – Sort, Search, and Counting Functions  Byte Swapping
Day 8 Matplotlib, Histogram Using Matplotlib  I/O With Numpy
Day 9 Matplotlib Library – Introduction, Pyplot API  Types Of Plots
Day 10 Seaborn Library
Day 11 SKLearn Library
Day 12 Google Colab Notebook
Day 13 Data Preparation & Visualisation
Day 14 Data Normalization Techniques
Day 15 Introduction to supervised learning algorithms.
Day 16Liver Disease Prediction – Logistic Regression
Day 17Flower Species Identification – SVM Algorithm.
Day 18Fake news detection – Naïve Baye’s
Day 19Android malware – Decision tree Algorithm.
Day 20 Credit_card Fraud detection – Random Forest Algorithm
Day 21 Employee Salary Prediction – Linear Regression Algorithm
Day 22 Advertisement and Sales Prediction – Multiple Linear Regression Algorithm.
Day 23 Agriculture Price Prediction – Random Forest Regression.
Day 24 Flower Species Data Visualization – PCA
Day 25 Market Basket Analysis – APRIARI
Day 26 Hate Speech Detection – NLTK
Day 27 – Loan Prediction Problem – XGBoost
Day 28Movie Review Classification RNN
Day 29Digits Classification – CNN
Day 30AI – Cart Pole – Reinforcement Learning

Day 1 Python Programming – Fundamentals

Day 2 Python – Tools  Syntaxes & Data Structures

Day 3  Machine Learning Concepts

Day 4  Pandas Library  Introduction

Day 5  Pandas – Data Structures

Day 6  Numpy library  Array Operations  Mathematical Functions

Day 7  Numpy  Sort , Search and Counting Functions  Byte Swapping

Day 8  Matplotlib , Histogram Using Matplotlib  I/O With Numpy

Day 9  Matplotlib Library  Introduction , Pyplot API  Types Of Plots

Day 10  Seaborn Library

Day 11  SKLearn Library

Day 12 Google Colab Notebook

Day 13 Data Preparation & Visualisation

Day 14  Data Normalization Techniques

Day 15 Introduction to supervised learning algorithms

Day 16Liver Disease Prediction – Logistic Regression

Day 17Flower Species Identification – SVM Algorithm

Day 18Fake news detection – Naïve Baye’s

Day 19  Android malware – Decision tree Algorithm

Day 20 Credit_card Fraud detection – Random Forest Algorithm

Day 21 Employee Salary Prediction – Linear Regression Algorithm

Day 22 Advertisement and Sales Prediction – Multiple Linear Regression Algorithm

Day 23  Agriculture Price Prediction – Random Forest Regression

Day 24  Flower Species Data Visualization – PCA

Day 25  Market Basket Analysis – APRIARI

Day 26  Hate Speech Detection – NLTK

Day 27 – Loan Prediction Problem – XGBoost

Day 28  Movie Review Classification RNN

Day 29  Digits Classification – CNN

Day 30AI – Cart Pole – Reinforcement Learning
I have completed day one class
I have completed my day 2 class
Mhacine learning easy to learn
It is a easy coding
My name is Kipkoech Philemon from Kenya, a student at Moi university. This is my day 26 of ML. Many thanks, I am learning
My name is Cathrine Loura A.I have registered my course on 30 days Machine Learning Master Class. and also registered in internship program.I attended all the classes.When i will get my certificate.kindly reply me…
Thank you…
Good
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