...
Full Bio
Today's Technology-Data Science
289 days ago
How to build effective machine learning models?
289 days ago
Why Robotic Process Automation Is Good For Your Business?
289 days ago
IoT-Advantages, Disadvantages, and Future
290 days ago
Look Artificial Intelligence from a career perspective
290 days ago
Every Programmer should strive for reading these 5 books
579738 views
Why you should not become a Programmer or not learn Programming Language?
239532 views
See the Salaries if you are willing to get a Job in Programming Languages without a degree?
152271 views
Have a look of some Top Programming Languages used in PubG
142521 views
Highest Paid Programming Languages With Highest Market Demand
137346 views
Online Machine Learning Courses with Verified Certificates
- Assemble machine learning algorithms from scratch!
- Build interesting applications using Javascript and ML techniques
- Understand how ML works without relying on mysterious libraries
- Optimize your algorithms with advanced performance and memory usage profiling
- Use the low-level features of Tensorflow JS to supercharge your algorithms
- Grow a strong intuition of ML best practices
- Machine Learning Engineers earn on average $166,000 - become an ideal candidate with this course!
- Solve any problem in your business, job or personal life with powerful Machine Learning models
- Train machine learning algorithms to predict house prices, identify handwriting, detect cancer cells & more
- Go from zero to hero in Python, Seaborn, Matplotlib, Scikit-Learn, SVM, unsupervised Machine Learning, etc
- Program in R
- Use R for Data Analysis
- Create Data Visualizations
- Use R to handle CSV, excel, SQL files or web scraping
- Use R to manipulate data easily
- Use R for Machine Learning Algorithms
- Use R for Data Science
- Build artificial neural networks with Tensorflow and Keras
- Classify images, data, and sentiments using deep learning
- Make predictions using linear regression, polynomial regression, and multivariate regression
- Data Visualization with MatPlotLib and Seaborn
- Implement machine learning at massive scale with Apache Spark's MLLib
- Understand reinforcement learning - and how to build a Pac-Man bot
- Classify data using K-Means clustering, Support Vector Machines (SVM), KNN, Decision Trees, Naive Bayes, and PCA
- Use train/test and K-Fold cross-validation to choose and tune your models
- Build a movie recommender system using item-based and user-based collaborative filtering
- Clean your input data to remove outliers
- Design and evaluate A/B tests using T-Tests and P-Values