medini bv
Interactive Machine Learning lessons with problem-solving focus
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medini bv
Bachelors degree
/ 55 min
About your data science tutor
I have pursued my master degree in Robotic Engineering from M S Ramaiah University of Applied Sciences Banglore and bachelors in Electronics and Communication Engineering. My roles and responsibilities and learning path towards Industry, - I worked as a intern at JSW steels Ballary by exploring the opportunities and learning's i was able to create the static Web-Page for the Company that can take the order for the customers for the products. - Further continuing the path i was intern at ComAvia System Technologies pvt. ltd Jalahalli Bangalore. During the period i has an extreme exposure to embedded system IOT. Also carried a mini project to publish the finger print data to cloud and retrieve it at the client and match the data. The main aim of the project is to make a cloud integration for the Bio metric attendance system. - I started to work as Robotics trainer for national and international students as freelancer in Wiingy Technology Pvt. Ltd during the period of M.Tech pursuing. Here i handled different course including Robotics, IOT, Arduino Programming, App development, STEM Education, Python, MATLAB, Machine learning etc. - After completion of M.Tech i joined Waveaxis Technology Pvt. Ltd as a Engineer Trainee in computer vision and Image processing. After the training period i prompted as Junior software developer. In this turning mode i had contributed my implementation 2 major project and 3 minor projects. Computer Vision, Machine Vision, Image processing, Halcon, Deep Learning, Python, OpenCV are skills of experience. - Further in the carrier moved ahead to join JyoSH AI solution Pvt, Ltd as a Senior Robotic Engineer for handling the areas of Embedded system design (H/W and S/W), Robotics, Robotics Vision, Machine learning and deep learning, Image processing, Sensor Integration, STM controller programming, Jetson GPU python coding for Machine vision in realtime, camera calibration and integration etc. - progressively i joined DLithe Consultancy Pvt. Ltd. as a Embedded Engineer. As a Embedded Engineer am handling the domains of Embedded Hardware, Software, Artificial Intelligence, Machine Learning and Robotics. being the technical expert and working on research and innovation in the domain to build the products for customer and also give the quality guidance for the students and teachers in enhancement of the industrial requirement and niche technology exploration.
medini graduated from GOVERNMENT ENGINEERING COLLEGE RAMANAGARA
Data Science tutor skills
Statistical analysis
Data visualization
Machine learning
Business intelligence
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Learner types for data science class
Data Science for intermediate
Data sciece class overview
As an expert of Artificial Intelligence, Machine Learning and Robotics and being the technical expert and working on research and innovation in the domain to build the products for customer and also give the quality guidance for the students and teachers in enhancement of the industrial requirement and niche technology exploration. I work as per the student knowledge and understanding. Making the concept clear making them independent after learning to solve any type of problems. In this exciting journey i trained more than 1000+ students in various domain receiving a constant support and encouragement for teaching. The way of teaching that i adopt has always been a grace for me to deal and comprehensive the content effective for all grades of students. I always believe in clear understanding and breakdown the problem to possible solution as minimal as possible to develop a competitive skills to solve the problem statement or coding skill. Trying to provide best support, helping them with the learning growth, supportive materials handing and doubt clarification anytime which i follow in the effective tutoring.
Data Science concepts taught by medini
Student and Tutor reviewed various supervised machine learning models, including logistic regression, decision trees, and SVMs. The Tutor then introduced deep learning, covering the fundamentals of neural networks, different architectures like CNNs and LSTMs, and the evolution to Large Language Models (LLMs) and Agentic AI. They explored tools like Groq and Flowise for building and testing AI agents, and the Tutor committed to sharing reference materials for further study on deep learning and agents.
Specialized Deep Learning Architectures: CNN
RNN
LSTM
Artificial Neural Network (ANN) Architecture & Training
From Transformers to Large Language Models (LLMs) & Agentic AI
LLM Ecosystem
Tools & Limitations
Introduction to Deep Learning & Neural Networks
The Student and Tutor reviewed and practiced problems related to RC circuits, focusing on discharging calculations for capacitance, charge, and current over time. The Tutor then introduced the fundamental concepts of RL circuits in a DC context, highlighting the time constant and distinguishing them from AC applications. The next session is planned to cover AC RL, RC, and RLC circuits, including phasor diagrams.
RC Circuit Discharging Analysis
Time Constants (τ) in RC and RL Circuits
RL Circuit Characteristics and DC Operation
Distinguishing DC and AC Circuit Analysis
Student and Tutor reviewed fundamental RC circuit concepts, including capacitor charging/discharging, time constants, and their application in AC-DC rectifier circuits. They solved several problems involving voltage, current, and time constant calculations for various RC circuits. The next session will cover additional RC circuit problem formats and then move on to RL and RLC circuits.
AC to DC Conversion and Filtering with Capacitors
Diode Biasing in Bridge Rectifier Circuits
Solving RC Circuit Problems
Capacitor Charging and Discharging Characteristics
Student and Tutor began a new topic on AC circuits, building upon the Student's recent success with DC circuit concepts like KVL, KCL, and superposition. They discussed the fundamental roles of resistors, capacitors, and inductors in circuits, then delved into the specifics of RC circuits, including the concept of the time constant and its implications for charging and discharging. The Tutor recommended the Student watch videos for further clarification on specific concepts before the next session.
Practical Implications of the Time Constant
Resistors in AC/DC Circuits
Capacitors: Charge Storage & AC Smoothing
Capacitor Charging and Discharging Dynamics
RC Circuits and the Time Constant (τ)
Inductors: Magnetic Fields & Voltage Transformation
The Tutor and Student explored supervised learning classification models, focusing on Logistic Regression. They discussed various classification algorithms, their applications, and implemented Logistic Regression using a heart disease dataset, including data cleaning, model evaluation via confusion matrices and classification reports, and interpretation of feature importance using SHAP values. The next session will be scheduled after the Student's interview.
SHAP Values for Model Interpretability
Model Evaluation in Classification
Logistic Regression for Classification
Classification Models
The Student and Tutor focused on the Maximum Power Transfer Theorem in electrical circuits. They reviewed its principles, derived the formula for maximum power transfer, and practiced solving problems involving various resistor networks to find the optimal load resistance and maximum power delivered. The next session will cover RLC circuits and related concepts like resonance.
Power Calculation Formulas
Thevenin Resistance (R<SUB>TH</SUB>) Calculation
Maximum Power Transfer Theorem
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