This scholarship will cover the following: Nation, Inuit, on/off reserve), a person of colour, LGTBQQ2, living with a disability, or a religious minority. Inspirit encourages and welcomes applications from people who identify as Indigenous (Métis, First Willing to share insights in a blog or other form about their experience at the conference for use by Inspirit.Must agree to participate in post-conference evaluation and online session hosted by Inspirit.Likely to benefit from learning outcomes of conference.Likely to apply learning to practice in Canada.Demonstrable practice in filmmaking or in using media to create positive social change.Able to attend for the entire conference (June 1-5, 2016).A travel bursary of up to $800 to support participants outside of B.C.Travel costs from Vancouver to Cortes Island.Full accommodation and meals at the Hollyhock Institute based on the shared dorm rate.Full Story Money Impact conference registration fee.Please fill out our online application by March 18th 2016.Īll successful applicants will be contacted by email on or before April 8, 2016. Story Money Impact will take place June 1-5, 2016 at the Hollyhock Institute on Cortes Island, B.C. It explores how these professions can synergize with funders who want maximum leverage for their resources and reach, while partnering with strategic innovators who can highlight those results with more robust evaluation tools. Structured around case studies from the front lines, Story Money Impact reveals best practices in the areas of documentary, digital content, and independent journalism. This intimate conference illuminates the spark of engagement at the core of these three pursuits. Media That Matters: Story Money Impact is a practical workshop for media-makers, principled funders, and highly motivated activists who want to ensure their work makes a difference. Media That Matters: Story Money Impact at the Hollyhock Institute on B.C.’s Cortes Island from June 1-5, I am also currently in Poly’s Girls Who Code club, which I really enjoy.The Inspirit Foundation is excited to offer 4 scholarships for young media-makers to attend this year’s “Though it is extremely broad, it interests me, and I love exploring all the things that can be done with it. “I am very interested in pursuing computer science as a career,” Triola said. She added, “I have not done any other similar AI projects at Poly, but I would love to do so sometime in the future!” “The second week,” Triola said, “I was placed with a group of students and a mentor to create our project, which used factors like keywords to determine whether a news article was fake.” I would love to use scikit-learn more in the future to find patterns in data sets regarding other issues like climate change.” I really enjoyed using scikit-learn because it allows the user to easily change parts of their model to make it predict more accurately. It allows users to create machine learning algorithms more easily than with Python alone. “We used technologies including scikit-learn to train machine learning models to do things like predict the price of cars based on a data set,” she said, explaining, “This is a technology that goes with the programming language Python. “Machine learning can also predict which posts on social media that individual users are more likely to click on this feature is often used in social media platforms that show the user personalized feed.” Creating the Learning Algorithim Machine learning can be trained to identify certain objects, and you may specifically encounter this with the facial recognition features in many devices.” Additionally, machine learning algorithms can quickly make many mathematical calculations, allowing them to give different levels of importance, or weights, to different factors or pieces of data when making predictions. With these patterns, machine learning can make predictions with much more accuracy than computers can. For instance, a computer could graph data on more than three axes while humans are limited to imagining in three dimensions. Broadly, machine learning is often defined as being computer programs that read through large amounts of data and recognize patterns that humans cannot. ” Asked what “machine learning” is, Triola explained, “Machine learning is similar to statistics, but there is overlap between the two categories, making it hard to draw a line between machine learning and statistics. “In the first week, I learned about machine learning with Python. Anyone who scrolls and clicks on their social media account teaches the machine.
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