24.12.2021, 22:32
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Data Science Bootcamp: Build & Deploy 45 Real World Projects
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 48.0 KHz
Language: English | Size: 15.3 GB | Duration: 33h 38m
Learn To Build & Deploy Machine Learning, Data Science, Deep Learning Projects (Python, Flask, Django, Heruko Cloud)
What you'll learn
Learn to use NumPy for Numerical Data
Understand the full product workflow for the machine learning lifecycle.
Master Machine Learning on Python, Make powerful analysis
Use Matplotlib to create fully customized data visualizations with Python.
Real life case studies and projects to understand how things are done in the real world
Learn to pre process data, clean data, and analyze large data
Construct a modern portfolio of data science and machine learning resume projects.
Learn which Machine Learning model to choose for each type of problem
Description
Machine learning is not like any other technology, but it is in many cases the only technology that can solve certain problems. We need to ensure that all people involved in the project have a common understanding of what is required, how the process works, and that we have a realistic view of what is possible with the tools at hand. To boil down all this to its core components we could consider a few important rules:
create a common ground of understanding, this will ensure the right mindset
state early how progress should be measured
communicate clearly how different machine learning concepts works
acknowledge and consider the inherited uncertainty, it is part of the process
In This Course, Solve Business Problems Using Data Science Practically. Learn To Build & Deploy Machine Learning, Data Science, Artificial Intelligence, Auto Ml, Deep Learning, Natural Language Processing (NLP) Web Applications Projects With Python (Flask, Django, Heruko, Streamlit Cloud).
We'll cover everything you need to know for the full data science and machine learning tech stack required at the world's top companies. Our students have gotten jobs at Dell, Google Developers, TCS, Wipro, and other top tech companies! We've structured the course using our experience teaching both online and in-person to deliver a clear and structured approach that will guide you through understanding not just how to use data science and machine learning libraries, but why we use them. This course is balanced between practical real-world case studies and mathematical theory behind the machine learning algorithms.
How much does a Data Scientist make in the United States?
The national average salary for a Data Scientist is US$1,20,718 per year in the United States, 2.8k salaries reported, updated on July 15, 2021 (source: glassdoor)
Salaries by Company, Role, Average Base Salary in (USD)
Facebook Data Scientist makes US$1,36,000/yr. Analyzed from 1,014 salaries.
Amazon Data Scientist makes US$1,25,704/yr. Analyzed from 307 salaries.
Apple Data Scientist makes US$1,53,885/yr. Analyzed from 147 salaries.
Google Data Scientist makes US$1,48,316/yr. Analyzed from 252 salaries.
IBM Data Scientist makes US$1,32,662/yr. Analyzed from 388 salaries.
Microsoft Data Scientist makes US$1,33,810/yr. Analyzed from 205 salaries.
Intel Corporation Data Scientist makes US$1,25,930/yr. Analyzed from 131 salaries.
In This Course, We Are Going To Work On 45 Real World Projects Listed Below:
Project-1: Pan Card Tempering Detector App -Deploy On Heroku
Project-2: Dog breed prediction Flask App
Project-3: Image Watermarking App -Deploy On Heroku
Project-4: Traffic sign classification
Project-5: Text Extraction From Images Application
Project-6: Plant Disease Prediction Streamlit App
Project-7: Vehicle Detection And Counting Flask App
Project-8: Create A Face Swapping Flask App
Project-9: Bird Species Prediction Flask App
Project-10: Intel Image Classification Flask App
Project-11: Sentiment Analysis Django App -Deploy On Heroku
Project-12: Attrition Rate Django Application
Project-13: Find Legendary Pokemon Django App -Deploy On Heroku
Project-14: Face Detection Streamlit App
Project-15: Cats Vs Dogs Classification Flask App
Project-16: Customer Revenue Prediction App -Deploy On Heroku
Project-17: Gender From Voice Prediction App -Deploy On Heroku
Project-18: Restaurant Recommendation System
Project-19: Happiness Ranking Django App -Deploy On Heroku
Project-20: Forest Fire Prediction Django App -Deploy On Heroku
Project-21: Build Car Prices Prediction App -Deploy On Heroku
Project-22: Build Affair Count Django App -Deploy On Heroku
Project-23: Build Shrooming Predictions App -Deploy On Heroku
Project-24: Google Play App Rating prediction With Deployment On Heroku
Project-25: Build Bank Customers Predictions Django App -Deploy On Heroku
Project-26: Build Artist Sculpture Cost Prediction Django App -Deploy On Heroku
Project-27: Build Medical Cost Predictions Django App -Deploy On Heroku
Project-28: Phishing Webpages Classification Django App -Deploy On Heroku
Project-29: Clothing Fit-Size predictions Django App -Deploy On Heroku
Project-30: Build Similarity In-Text Django App -Deploy On Heroku
Project-31: Heart Attack Risk Prediction Using Eval ML (Auto ML)
Project-32: Credit Card Fraud Detection Using Pycaret (Auto ML)
Project-33: Flight Fare Prediction Using Auto SK Learn (Auto ML)
Project-34: Petrol Price Forecasting Using Auto Keras
Project-35: Bank Customer Churn Prediction Using H2O Auto ML
Project-36: Air Quality Index Predictor Using TPOT With End-To-End Deployment (Auto ML)
Project-37: Rain Prediction Using ML models & PyCaret With Deployment (Auto ML)
Project-38: Pizza Price Prediction Using ML And EVALML(Auto ML)
Project-39: IPL Cricket Score Prediction Using TPOT (Auto ML)
Project-40: Predicting Bike Rentals Count Using ML And H2O Auto ML
Project-41: Concrete Compressive Strength Prediction Using Auto Keras (Auto ML)
Project-42: Bangalore House Price Prediction Using Auto SK Learn (Auto ML)
Project-43: Hospital Mortality Prediction Using PyCaret (Auto ML)
Project-44: Employee Evaluation For Promotion Using ML And Eval Auto ML
Project-45: Drinking Water Potability Prediction Using ML And H2O Auto ML
Tip (Not Mandatory): Create A 45 Days Study Plan, Spend 1-2hrs Per Day, Build 45 Projects In 45 Days.
The Only Course You Need To Become A Data Scientist, Get Hired And Start A New Career
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