Machine Learning Training
(Duration 3 Months)
An Overview
Machine learning courses focus on teaching individuals the principles, techniques, and applications of machine learning, which is a subset of artificial intelligence (AI). These courses typically cover topics such as data preprocessing, feature selection, model training and evaluation, and various machine learning algorithms and Machine Learning Projects etc.
Advantages
In the recent past, Machine Learning technology has fairly attracted a wide number of IT professionals. It is because most of the businesses of the different sectors such as the Automotive industry, Robotics, Banking and Finance, Information Technology, Gaming, Media, and Entertainment use Machine Learning Techniques to enhance their business.
Based on the reports submitted by Gartner Inc, it is stated that by the end of 2020 Machine Learning Technology will create around 2.3 million jobs. In addition to this, it is stated that Machine Learning will create 9.8 times more jobs than it was three years back. The reputed companies that hire the Machine Learning Engineers are Google, Amazon, Adobe, Facebook, Apple, Bosch Group, Adobe, Accenture, Wipro, Uber, and JP Morgan Chase & Co
Syllabus
Download Syllabus - Introduction to Machine Learning
- Introduction to Data in Machine Learning
- Applications of Machine Learning
- Best Python libraries for Machine Learning
- Difference Between ML & AI
- Difference Between ML & DL
- Understanding Data Processing
- Generate Test Datasets for Machine learning
- Overview of Data Cleaning
- Feature Scaling – Part 1
- Feature Engineering- Scaling, Normalization, and Standardization
- Label Encoding in Python
- One Hot Encoding in Machine Learning
- Linear Algebra Operations
- Linear Regression in Machine learning
- Mathematics Mean, Variance and Standard Deviation
- Understanding Hypothesis Testing
- Find a matrix or vector norm using NumPy
- Separating Hyperplanes in SVM
- Types of Supervised learning
- Classification vs Regression in Machine Learning
- Getting started with Classification
- Basic Concept of Classification (Data Mining)
- Types of Regression Techniques in ML
- Gradient Descent algorithm and its variants
- Getting started with Classification
- Logistic Regression using Python
- Why Logistic Regression in Classification
- Introduction to Support Vector Machines (SVM)
- Decision Tree
- Supervised and Unsupervised learning
- Clustering in Machine Learning
- Different Types of Clustering Algorithm
- K means Clustering – Introduction
- Fuzzy Clustering
- Introduction of Dimensionality Reduction
- Approaches of Dimension Reduction
- Under fitting and Over fitting
- Common techniques of Dimensionality Reduction
- Introduction to Natural Language Processing
- Text Preprocessing in Python Set – 1
- Text Preprocessing in Python Set 2
- Removing stop words with NLTK in Python
- Stemming words with NLTK
- Lemmatization with NLTK
- Lemmatization with TextBlob
- Introduction to Artificial Neutral Networks
- TArtificial Neutral Networks (Network Architectures)
- Activation functions in Neural Networks
- Introduction
- Creating numpy array
- Numpy array manipulation
- Matrix in numpy
- Operations on numpy
- Reshaping numpy array
- Arithmetic Operation on numpy
- Sorting and searching in numpy
- Introduction
- Creating objects
- Viewing data
- Manipulating data
- Selection
- Working with text data
- Working with csv & Excel files
- Data analysis using pandas
- Importing the module
- Python simple calculator using tkinter
- Simple Registration form using tkinter
- Simple Login form using tkinter
- Python GUI – tkinter
- Inserting Variables
- Mysql connection
- Python database management
- SQL using python SQlite
- Django basic
- Views in django
- Django URLs
- Django Template
- Django Forms
- Django models
- Django projects
Machine Learning Projects
- Disease Prediction Using Machine Learning
- Predicting Stock Price Direction using Support Vector Machines
- Face and Hand Landmarks Detection using Python – Mediapipe, OpenCV
- Wine Quality Prediction – Machine Learning
- Human Activity Recognition
- Twitter Sentiment Analysis