Akbar's Data Science Journey

Akbar, originally from Azerbaijan and now living in Germany, shares his journey from working in marketing and sales to pursuing a career in data science. He discusses his interest in machine learning and deep learning, leading to his final project on image recognition using convolutional neural networks. Akbar explains the steps taken to develop and optimize the model, including data augmentation and using pre-trained models. He demonstrates the app he created using Streamlit, which predicts dog breeds from images. The presentation concludes with a thank you to the audience.

What was Akbar's field of study before he transitioned to data science?

• Economics

• Computer Science

• Physics

• Mathematics

Which course did Akbar enroll in to pursue his interest in data science?

• Udacity

• edX

• VPS Coding School

• Coursera

What was the focus of Akbar's final project in his data science course?

• Time Series Analysis

• Image Recognition

• Natural Language Processing

• Reinforcement Learning

Which dataset did Akbar use for his image recognition project?

• MNIST

• ImageNet

• Kaggle Taco Dataset

• CIFAR-10

What technique did Akbar use to increase the amount of data for his model?

• Data Synthesis

• Data Reduction

• Data Augmentation

• Data Normalization

Which pre-trained model did Akbar choose as the base for his image recognition project?

• Inception V3

• VGG16

• MobileNet

• ResNet

What optimizer did Akbar use for tuning the hyperparameters of his model?

• RMSprop

• SGD

• Adagrad

• Adam

What framework did Akbar use to create the app for his project?

• Django

• Flask

• Streamlit

• React

What functionality does Akbar's app provide?

• Recognizing dog breeds from images

• Predicting weather patterns

• Translating languages

• Analyzing stock market trends

What is displayed on the home page of Akbar's app?

• A dog image and app information

• A welcome message

• A list of dog breeds

• User testimonials