Do you want to do Machine Learning using Python, but you’re having trouble getting started? In this post, you will complete your first machine learning project using Python. If you are a machine learning beginner and looking to finally get started using Python, this tutorial was designed for you.
Workshop Plan Day wise
[ult_tab_element tab_style=”Style_3″ tab_animation=”Slide-Horizontal” tab_title_color=”#333333″ tab_background_color=”#ededed” tab_hover_title_color=”#ededed” tab_hover_background_color=”#333333″ acttab_title=”#ffffff” acttab_background=”#c5202e” tabs_border_radius=”0″ tab_describe_color=”#333333″ enable_bg_color=”#fcfcfc” container_border_style1=”border-style:none;|border-width:1px;border-radius:3px;|border-color:#e2e2e2;” title_font_style=”font-weight:bold;” title_font_size=”desktop:16px;” main_heading_font_family=”font_family:|font_call:”][single_tab icon=”none” title=”Day 1 | Session 1 & 2″ tab_id=”01″]What is machine learning?
- Introduction to machine learning
- Understanding the need
- Understanding Big data and machine learning
- Running machine learning under Linux platform
- Why Linux is important for machine learning with respect to future
- Role of Python and R programming in this domain
- Basic Introduction of Python syntax and programming logics
- Deep dive with Supervised and Unsupervised learning
Python programming
- Basic of python and why python for machine learning
- Installation of software on different OS.
- Understanding basic syntax with data types
- Number, string, list, tuple and dictionary
- Loops, conditions
- User input and user defined functions
- How to use libraries
- Creating and importing own library
Installation of Python Libraries in System Numpy
- Formation of Arrays and its operation
- Working with multidimensional arrays using numpy
- Data formation and matrix manipulations
- Use of Numpy in Data Science
Matplotlib
- Data Visualisation in linear graphs
- Bar Graph
- Pie Charts
- Multiple data visualisation in one plotz
Supervised and Unsupervised Learning
Working with Python for ML
Types of learning
- Supervised Learning lab with Hello World Program
- Classification and regression
- Entropy and Information Gain
- Training your machine with real time data sets
Project:- Creating own ML datasets and it’s implementation
Working with classification algos
- Decision Tree
- Decision Tree algo deep dive
Pandas
- Introduction to dataframes
- Reading / writing data files
- Structure of dataframes
- Use of dataframes with ML
- Datasets reading from Scikit-Learn
Project:- Designing of ML system for real time datasets
OpenCV
- Image Processing with Python
- Image Read and type conversions
Deep Learning, Image search and recognition
- Concept of neural network
- Understanding neural networks
- Searching for image
- Loading image with cloud library
- Registering image for training model
- Training image datasets
- Recognition of different images to detect face
- Deregistering images from cloud library
Project:- Face Recognition System over the cloud using ML
Query Session
Project Details
- Raspberry Pi 3B (Refundable)
- Memory Card 16 GB (Refundable)
- USB Cable
- Bulb & Holder (2 set)
- Connecting cable & Wires
- Relay board
- LAN cable (type 5)
- Screw Driver
- A seminar hall/Class room with seating capacity of 100 students
- One projector.
- 2 Collar mike with sound system.
- White board and marker.
- Workshop coordinators(3-5)
- Laptop charging points.
- One laptop/PC to each group.
- Acquaint yourself with practical knowledge.
- Workshop taken by Exceptionally Qualified and Professional Trainers actively involved in Research & Development.
- Learn your Area of Interest directly from Industry Experts.
- Scales up your CV/ Resume in Technical while boosting your Logical Abilities.
- Brings Confidence in you for Technical rounds of Interview.
- Lifetime assistance on any of your projects.
- Certificate of Participation.
- Certificate of Coordination.
- Certificate of Appreciation to College.
- Relevant Software.
- Study Material (Soft Copy) FREE.
- A TechieNest notepad
To Organize workshop in Your Campus
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