You will get COVID 19 forecasting using john Hopkins data
Project details
In my data science projects, I’ve leveraged cutting-edge machine learning techniques to solve complex problems. some key highlights:
Project Scope:
Developed predictive models for various domains, including healthcare, finance, and e-commerce.
Conducted exploratory data analysis (EDA) to understand underlying patterns and relationships.
Technological Expertise:
Proficient in Python, utilizing libraries such as Pandas, Scikit-learn, and TensorFlow.
Implemented regression, classification, and clustering algorithms.
Impact and Results:
Achieved significant accuracy improvements in customer churn prediction (up to 90%).
Uncovered actionable insights from sentiment analysis of social media data.
Innovation and Challenges:
Innovated by integrating deep learning models for image recognition tasks.
Overcame challenges related to imbalanced datasets and feature engineering.
Commitment to data-driven decision-making and continuous learning drives success. Let’s discuss how I can collaborate on your next project! 🚀
Project Scope:
Developed predictive models for various domains, including healthcare, finance, and e-commerce.
Conducted exploratory data analysis (EDA) to understand underlying patterns and relationships.
Technological Expertise:
Proficient in Python, utilizing libraries such as Pandas, Scikit-learn, and TensorFlow.
Implemented regression, classification, and clustering algorithms.
Impact and Results:
Achieved significant accuracy improvements in customer churn prediction (up to 90%).
Uncovered actionable insights from sentiment analysis of social media data.
Innovation and Challenges:
Innovated by integrating deep learning models for image recognition tasks.
Overcame challenges related to imbalanced datasets and feature engineering.
Commitment to data-driven decision-making and continuous learning drives success. Let’s discuss how I can collaborate on your next project! 🚀
Machine Learning Tools
Keras, NumPy, OpenCV, pandas, Python, Python Scikit-Learn, scikit-learn, XGBoostWhat's included
| Service Tiers |
Starter
$30
|
Standard
$60
|
Advanced
$90
|
|---|---|---|---|
| Delivery Time | 3 days | 6 days | 9 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 2 | 3 |
Number of Graphs/Charts | 1 | 3 | 5 |
Model Validation/Testing | - | ||
Model Documentation | - | - | |
Data Source Connectivity | |||
Source Code |
Optional add-ons
You can add these on the next page.
Additional Revision
+$10
Additional Model Variation
(+ 2 Days)
+$40
Additional Scenario
(+ 2 Days)
+$40
Additional Graph/Chart
(+ 1 Day)
+$15
Model Validation/Testing
(+ 2 Days)
+$20
Model Documentation
(+ 2 Days)
+$20Frequently asked questions
About Ijaz
data science with hands on Machine learning.
Peshawar, Pakistan - 8:39 pm local time
Analytically minded self-starter with
significant data science experience
collaborating with cross-functional
teams and ensuring the accuracy
and integrity of data and actionable
insight. I am eager to contribute my
skills in quantitative analysing and
experimentation to enhance the
experience of users around the
world
Steps for completing your project
After purchasing the project, send requirements so Ijaz can start the project.
Delivery time starts when Ijaz receives requirements from you.
Ijaz works on your project following the steps below.
Revisions may occur after the delivery date.
Importing Data
Data must be imported, and will be cleaned and prepared for picking up features
Data Exploration
Secondly, exploring process will take place in which data will be shown in different shapes using pie, bar, and line graphs depend on the data.