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- 101 sections • 731 lectures • 105h 39m total length
- 2022-11 | e-Learning | English | MP4, ZIP | 51.44 GB
- Build 100 Projects in 100 Days - Data Science, Machine Learning, Deep Learning (Python, Flask, Django, AWS, Heruku Cloud).
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- -------------------------
- What you'll learn
- - Have a great intuition of many Machine Learning models
- - Know which Machine Learning model to choose for each type of problem
- - Implement Machine Learning Algorithms
- - Create supervised machine learning algorithms to predict classes.
- - Understand the full product workflow for the machine learning lifecycle.
- - Explore how to deploy your machine learning models.
- - Learn which Machine Learning model to choose for each type of problem
- - Real life case studies and projects to understand how things are done in the real world
- - Learn to use NumPy for Numerical Data
- - Use Matplotlib to create fully customized data visualizations with Python.
- - Explore large datasets and wrangle data using Pandas
- - Learn to use Seaborn for statistical plots
- Requirements
- - Basic knowledge of machine learning
- Description
- 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, Heroku, AWS, Azure, GCP, IBM Watson, Streamlit Cloud).
- We have been able to process such a voluminous amount of data. We are able to analyze and draw insights from this data owing to these advanced computational systems.
- However, despite all these advancements, data remains a vast ocean that is growing every second. While the huge abundance of data can prove useful for the industries, the problem lies in the ability to use this data.
- As mentioned above, data is fuel but it is a raw fuel that needs to be converted into useful fuel for the industries. In order to make this raw fuel useful, industries require Data Scientists. Therefore, knowledge of data science is a must if you wish to use this data to help companies make powerful decisions.
- According to Glassdoor, the average salary for a Data Scientist is $117,345/yr. This is above the national average of $44,564. Therefore, a Data Scientist makes 163% more than the national average salary.
- This makes Data Science a highly lucrative career choice. It is mainly due to the dearth in Data Scientists resulting in a huge income bubble.
- Since Data Science requires a person to be proficient and knowledgeable in several fields like Statistics, Mathematics and Computer Science, the learning curve is quite steep. Therefore, the value of a Data Scientist is very high in the market.
- A Data Scientist enjoys the position of prestige in the company. The company relies on his expertise to make data-driven decisions and enable them to navigate in the right direction.
- Furthermore, the role of a Data Scientist depends on the specialization of his employer company. For example – A commercial industry will require a data scientist to analyze their sales.
- A health-care company will require data scientists to help them analyze genomic sequences. The salary of a Data Scientist depends on his role and type of work he has to perform. It also depends on the size of the company which is based on the amount of data they utilize.
- Still, the pay scale of Data Scientist is way above other IT and management sectors. However, the salary observed by Data Scientists is proportional to the amount of work that they must put in. Data Science needs hard work and requires a person to be thorough with his/her skills.
- In This Course, We Are Going To Work On 100 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: Language Translator App Using IBM Cloud Service -Deploy On Heroku
- Project-12: Predict Views On Advertisement Using IBM Watson -Deploy On Heroku
- Project-13: Laptop Price Predictor -Deploy On Heroku
- Project-14: WhatsApp Text Analyzer -Deploy On Heroku
- Project-15: Course Recommendation System -Deploy On Heroku
- Project-16: IPL Match Win Predictor -Deploy On Heroku
- Project-17: Body Fat Estimator App -Deploy On Microsoft Azure
- Project-18: Campus Placement Predictor App -Deploy On Microsoft Azure
- Project-19: Car Acceptability Predictor -Deploy On Google Cloud
- Project-20: Book Genre Classification App -Deploy On Amazon Web Services
- Project 21: DNA classification for finding E.Coli - Deploy On AWS
- Project 22: Predict the next word in a sentence. - AWS - Deploy On AWS
- Project 23: Predict Next Sequence of numbers using LSTM - Deploy On AWS
- Project 24: Keyword Extraction from text using NLP - Deploy On Azure
- Project 25: Correcting wrong spellings - Deploy On Azure
- Project 26: Music popularity classification - Deploy On Google App Engine
- Project 27: Advertisement Classification - Deploy On Google App Engine
- Project 28: Image Digit Classification - Deploy On AWS
- Project 29: Emotion Recognition using Neural Network - Deploy On AWS
- Project 30: Breast cancer Classification - Deploy On AWS
- Project-31: Sentiment Analysis Django App -Deploy On Heroku
- Project-32: Attrition Rate Django Application
- Project-33: Find Legendary Pokemon Django App -Deploy On Heroku
- Project-34: Face Detection Streamlit App
- Project-35: Cats Vs Dogs Classification Flask App
- Project-36: Customer Revenue Prediction App -Deploy On Heroku
- Project-37: Gender From Voice Prediction App -Deploy On Heroku
- Project-38: Restaurant Recommendation System
- Project-39: Happiness Ranking Django App -Deploy On Heroku
- Project-40: Forest Fire Prediction Django App -Deploy On Heroku
- Project-41: Build Car Prices Prediction App -Deploy On Heroku
- Project-42: Build Affair Count Django App -Deploy On Heroku
- Project-43: Build Shrooming Predictions App -Deploy On Heroku
- Project-44: Google Play App Rating prediction With Deployment On Heroku
- Project-45: Build Bank Customers Predictions Django App -Deploy On Heroku
- Project-46: Build Artist Sculpture Cost Prediction Django App -Deploy On Heroku
- Project-47: Build Medical Cost Predictions Django App -Deploy On Heroku
- Project-48: Phishing Webpages Classification Django App -Deploy On Heroku
- Project-49: Clothing Fit-Size predictions Django App -Deploy On Heroku
- Project-50: Build Similarity In-Text Django App -Deploy On Heroku
- Project-51: Black Friday Sale Project
- Project-52: Sentiment Analysis Project
- Project-53: Parkinson’s Disease Prediction Project
- Project-54: Fake News Classifier Project
- Project-55: Toxic Comment Classifier Project
- Project-56: IMDB Movie Ratings Prediction
- Project-57: Indian Air Quality Prediction
- Project-58: Covid-19 Case Analysis
- Project-59: Customer Churning Prediction
- Project-60: Create A ChatBot
- Project-61: Video Game sales Analysis
- Project-62: Zomato Restaurant Analysis
- Project-63: Walmart Sales Forecasting
- Project-64: Sonic wave velocity prediction using Signal Processing Techniques
- Project-65: Estimation of Pore Pressure using Machine Learning
- Project-66: Audio processing using ML
- Project-67: Text characterisation using Speech recognition
- Project-68: Audio classification using Neural networks
- Project-69: Developing a voice assistant
- Project-70: Customer segmentation
- Project-71: FIFA 2019 Analysis
- Project-72: Sentiment analysis of web scrapped data
- Project-73: Determining Red Vine Quality
- Project-74: Customer Personality Analysis
- Project-75: Literacy Analysis in India
- Project-76: Heart Attack Risk Prediction Using Eval ML (Auto ML)
- Project-77: Credit Card Fraud Detection Using Pycaret (Auto ML)
- Project-78: Flight Fare Prediction Using Auto SK Learn (Auto ML)
- Project-79: Petrol Price Forecasting Using Auto Keras
- Project-80: Bank Customer Churn Prediction Using H2O Auto ML
- Project-81: Air Quality Index Predictor Using TPOT With End-To-End Deployment (Auto ML)
- Project-82: Rain Prediction Using ML models & PyCaret With Deployment (Auto ML)
- Project-83: Pizza Price Prediction Using ML And EVALML(Auto ML)
- Project-84: IPL Cricket Score Prediction Using TPOT (Auto ML)
- Project-85: Predicting Bike Rentals Count Using ML And H2O Auto ML
- Project-86: Concrete Compressive Strength Prediction Using Auto Keras (Auto ML)
- Project-87: Bangalore House Price Prediction Using Auto SK Learn (Auto ML)
- Project-88: Hospital Mortality Prediction Using PyCaret (Auto ML)
- Project-89: Employee Evaluation For Promotion Using ML And Eval Auto ML
- Project-90: Drinking Water Potability Prediction Using ML And H2O Auto ML
- Project-91: Image Editor Application With OpenCV And Tkinter
- Project-92: Brand Identification Game With Tkinter And Sqlite3
- Project-93: Transaction Application With Tkinter And Sqlite3
- Project-94: Learning Management System With Django
- Project-95: Create A News Portal With Django
- Project-96: Create A Student Portal With Django
- Project-97: Productivity Tracker With Django And Plotly
- Project-98: Create A Study Group With Django
- Project-99: Building Crop Guide Application with PyQt5, SQLite
- Project-100: Building Password Manager Application With PyQt5, SQLite
- Tip: Create a 50 Days Study Plan or 100 Day Study Plan, Spend 1-3hrs Per Day, Build 100 Projects in 50 Days or 100 Projects in 100 Days.
- The Only Course You Need to Become a Data Scientist, Get Hired and Start a New Career
- Note (Read This): This Course Is Worth Of Your Time And Money, Enroll Now Before Offer Expires.
- Who this course is for:
- - Beginners in data science
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