Pickl AI

JULY 10, 2024

Introduction Artificial Intelligence (AI) and Machine Learning are revolutionising industries by enabling smarter decision-making and automation. In this fast-evolving field, continuous learning and upskilling are crucial for staying relevant and competitive. Topics include Reinforcement Learning, NLP, and Deep Learning.

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Pickl AI

SEPTEMBER 3, 2024

ReLU is widely used in Deep Learning due to its simplicity and effectiveness in mitigating the vanishing gradient problem. Tanh (Hyperbolic Tangent): This function maps input values to a range between -1 and 1, providing a smooth gradient for learning.

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AWS Machine Learning Blog

OCTOBER 2, 2024

For example, you can use AWS data analytics services such as Amazon Redshift for data warehousing, AWS Glue for data integration, and Amazon QuickSight for business intelligence (BI). Leveraging her expertise in Computer Vision and Deep Learning, she empowers customers to harness the power of the ML in AWS cloud efficiently.

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Pickl AI

SEPTEMBER 23, 2024

AI, particularly Machine Learning and Deep Learning uses these insights to develop intelligent models that can predict outcomes, automate processes, and adapt to new information. Deep Learning: Advanced neural networks drive Deep Learning , allowing AI to process vast amounts of data and recognise complex patterns.

Data Science 52

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Pickl AI

APRIL 18, 2023

Continuous Learning The Data Science domain is evolving, and the best Data Science course will always emphasise providing updated knowledge and skills. Check if the course provider organizes hackathons and Datathons.

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Pickl AI

JUNE 19, 2024

Look for opportunities in business intelligence, market research, or any role that involves data analysis and interpretation. For instance, courses focusing on big data might require knowledge of Hadoop or Spark, while those emphasizing machine learning might delve into deep learning frameworks like TensorFlow or PyTorch.

Data Science 52

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Pickl AI

APRIL 26, 2024

It showcases expertise and demonstrates a commitment to continuous learning and growth. It is essential to provide a unified data view and enable business intelligence and analytics. Are there any areas in data analytics where you want to improve or learn more? Explain the Extract, Transform, Load (ETL) process.

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